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wszystkich: 850
Katalog Publikacji
Rok 2025
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AI-Driven Sustainability in Agriculture and Farming
PublikacjaIn this chapter, we discuss the role of artificial intelligence (AI) in promoting sustainable agriculture and farming. Three main themes run through the chapter. First, we review the state of the art of smart farming and explore the transformative impact of AI on modern agricultural practices, focusing on its contribution to sustainability. With this in mind, our analysis focuses on topics such as data collection and storage, AI...
Rok 2024
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A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublikacjaOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
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A review of explainable fashion compatibility modeling methods
PublikacjaThe paper reviews methods used in the fashion compatibility recommendation domain. We select methods based on reproducibility, explainability, and novelty aspects and then organize them chronologically and thematically. We presented general characteristics of publicly available datasets that are related to the fashion compatibility recommendation task. Finally, we analyzed the representation bias of datasets, fashion-based algorithms’...
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublikacjaIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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An intelligent cellular automaton scheme for modelling forest fires
PublikacjaForest fires have devastating consequences for the environment, the economy and human lives. Understanding their dynamics is therefore crucial for planning the resources allocated to combat them effectively. In a world where the incidence of such phenomena is increasing every year, the demand for efficient and accurate computational models is becoming increasingly necessary. In this study, we perform a revision of an initial proposal...
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Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublikacjaMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublikacjaThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Holistic collision avoidance decision support system for watchkeeping deck officers
PublikacjaThe paper presents a 3-stage synthesis-based Decision Support System for watchkeeping deck officers. Its functional scope covers conflict detection, maneuver selection, and maneuver execution, all phases supplemented by collision alerts. First, a customized elliptic ship domain is used for checking if both OS and TS will have enough free space. A survey-based navigators’ declarative OS arena is then used to determine the time at...
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LSA Is not Dead: Improving Results of Domain-Specific Information Retrieval System Using Stack Overflow Questions Tags
PublikacjaThe paper presents the approach to using tags from Stack Overflow questions as a data source in the process of building domain-specific unsupervised term embeddings. Using a huge dataset of Stack Overflow posts, our solution employs the LSA algorithm to learn latent representations of information technology terms. The paper also presents the Teamy.ai system, currently developed by Scalac company, which serves as a platform that...
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Performance and Energy Aware Training of a Deep Neural Network in a Multi-GPU Environment with Power Capping
PublikacjaIn this paper we demonstrate that it is possible to obtain considerable improvement of performance and energy aware metrics for training of deep neural networks using a modern parallel multi-GPU system, by enforcing selected, non-default power caps on the GPUs. We measure the power and energy consumption of the whole node using a professional, certified hardware power meter. For a high performance workstation with 8 GPUs, we were...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublikacjaIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublikacjaBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
Rok 2023
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A Formal Approach to Model the Expansion of Natural Events: The Case of Infectious Diseases
PublikacjaA formal approach to modeling the expansion of natural events is presented in this paper. Since the mathematical, statistical or computational methods used are not relevant for development, a modular framework is carried out that guides from the external observation down to the innermost level of the variables that have to appear in the future mathematical-computational formalization. As an example we analyze the expansion of Covid-19....
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A multithreaded CUDA and OpenMP based power‐aware programming framework for multi‐node GPU systems
PublikacjaIn the paper, we have proposed a framework that allows programming a parallel application for a multi-node system, with one or more GPUs per node, using an OpenMP+extended CUDA API. OpenMP is used for launching threads responsible for management of particular GPUs and extended CUDA calls allow to manage CUDA objects, data and launch kernels. The framework hides inter-node MPI communication from the programmer who can benefit from...
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AngioScore: An artificial intelligence tool to assess coronary artery lesions
PublikacjaThe functionality scope of the AngioScore tool in semi-automatic assessment of stenoses according to the SYNTAX scale was presented. An evaluation of the preliminary accuracy of AngioScore in lesion assessment was performed.
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Antipsychotic drug prescription sequence analysis in relation to death occurrence and cardiometabolic drug usage: A retrospective longitudinal study
PublikacjaThe potential role of antipsychotics in increasing cardiovascular risk of mortality is still debated. The aim of this study was to assess the death risk associated with sequences of first-generation antipsychotic (FGA) and second-generation antipsychotic (SGA) prescriptions, including clozapine and lithium, and drugs for cardiometabolic diseases. We conducted a retrospective longitudinal analysis involving 84,881 patients who received...
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Application of a stochastic compartmental model to approach the spread of environmental events with climatic bias
PublikacjaWildfires have significant impacts on both environment and economy, so understanding their behaviour is crucial for the planning and allocation of firefighting resources. Since forest fire management is of great concern, there has been an increasing demand for computationally efficient and accurate prediction models. In order to address this challenge, this work proposes applying a parameterised stochastic model to study the propagation...
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Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA
PublikacjaLarge-scale Graph Convolutional Network (GCN) inference on traditional CPU/GPU systems is challenging due to a large memory footprint, sparse computational patterns, and irregular memory accesses with poor locality. Intel’s Programmable Integrated Unffied Memory Architecture (PIUMA) is designed to address these challenges for graph analytics. In this paper, a detailed characterization of GCNs is presented using the Open-Graph Benchmark...
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Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublikacjaAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublikacjaThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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Dynamic GPU power capping with online performance tracing for energy efficient GPU computing using DEPO tool
PublikacjaGPU accelerators have become essential to the recent advance in computational power of high- performance computing (HPC) systems. Current HPC systems’ reaching an approximately 20–30 mega-watt power demand has resulted in increasing CO2 emissions, energy costs and necessitate increasingly complex cooling systems. This is a very real challenge. To address this, new mechanisms of software power control could be employed. In this...
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Efficient parallel implementation of crowd simulation using a hybrid CPU+GPU high performance computing system
PublikacjaIn the paper we present a modern efficient parallel OpenMP+CUDA implementation of crowd simulation for hybrid CPU+GPU systems and demonstrate its higher performance over CPU-only and GPU-only implementations for several problem sizes including 10 000, 50 000, 100 000, 500 000 and 1 000 000 agents. We show how performance varies for various tile sizes and what CPU–GPU load balancing settings shall be preferred for various domain...
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Empirical analysis of tree-based classification models for customer churn prediction
PublikacjaCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
PublikacjaHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...
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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublikacjaIn this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...
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General Provisioning Strategy for Local Specialized Cloud Computing Environments
PublikacjaThe well-known management strategies in cloud computing based on SLA requirements are considered. A deterministic parallel provisioning algorithm has been prepared and used to show its behavior for three different requirements: load balancing, consolidation, and fault tolerance. The impact of these strategies on the total execution time of different sets of services is analyzed for randomly chosen sets of data. This makes it possible...
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Long‐time scale simulations of virus‐like particles from three human‐norovirus strains
PublikacjaThe dynamics of the virus like particles (VLPs) corresponding to the GII.4 Houston, GII.2 SMV, and GI.1 Norwalk strains of human noroviruses (HuNoV) that cause gastroenteritis was investigated by means of long-time (about 30 μs in the laboratory timescale) molecular dynamics simulations with the coarse-grained UNRES force field. The main motion of VLP units turned out to be the bending at the junction between the P1 subdomain (that...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublikacjaMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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Optimization of Bread Production Using Neuro-Fuzzy Modelling
PublikacjaAutomation of food production is an actively researched domain. One of the areas, where automation is still not progressing significantly is bread making. The process still relies on expert knowledge regarding how to react to procedure changes depending on environmental conditions, quality of the ingredients, etc. In this paper, we propose an ANFIS-based model for changing the mixer speed during the kneading process. Although the...
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Optimization of parallel implementation of UNRES package for coarse‐grained simulations to treat large proteins
PublikacjaWe report major algorithmic improvements of the UNRES package for physics-based coarse-grained simulations of proteins. These include (i) introduction of interaction lists to optimize computations, (ii) transforming the inertia matrix to a pentadiagonal form to reduce computing and memory requirements, (iii) removing explicit angles and dihedral angles from energy expressions and recoding the most time-consuming energy/force terms...
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Optymalizacja zasobów chmury obliczeniowej z wykorzystaniem inteligentnych agentów w zdalnym nauczaniu
PublikacjaRozprawa dotyczy optymalizacji zasobów chmury obliczeniowej, w której zastosowano inteligentne agenty w zdalnym nauczaniu. Zagadnienie jest istotne w edukacji, gdzie wykorzystuje się nowoczesne technologie, takie jak Internet Rzeczy, rozszerzoną i wirtualną rzeczywistość oraz deep learning w środowisku chmury obliczeniowej. Zagadnienie jest istotne również w sytuacji, gdy pandemia wymusza stosowanie zdalnego nauczania na dużą skalę...
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Parallel implementation of a Sailing Assistance Application in a Cloud Environment
PublikacjaSailboat weather routing is a highly complex problem in terms of both the computational time and memory. The reason for this is a large search resulting in a multitude of possible routes and a variety of user preferences. Analysing all possible routes is only feasible for small sailing regions, low-resolution maps, or sailboat movements on a grid. Therefore, various heuristic approaches are often applied, which can find solutions...
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Performance assessment of OpenMP constructs and benchmarks using modern compilers and multi-core CPUs
PublikacjaConsidering ongoing developments of both modern CPUs, especially in the context of increasing numbers of cores, cache memory and architectures as well as compilers there is a constant need for benchmarking representative and frequently run workloads. The key metric is speed-up as the computational power of modern CPUs stems mainly from using multiple cores. In this paper, we show and discuss results from running codes such as:...
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Photos and rendered images of LEGO bricks
PublikacjaThe paper describes a collection of datasets containing both LEGO brick renders and real photos. The datasets contain around 155,000 photos and nearly 1,500,000 renders. The renders aim to simulate real-life photos of LEGO bricks allowing faster creation of extensive datasets. The datasets are publicly available via the Gdansk University of Technology “Most Wiedzy” institutional repository. The source files of all tools used during...
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Previous Opinions is All You Need - Legal Information Retrieval System
PublikacjaWe present a system for retrieving the most relevant legal opinions to a given legal case or question. To this end, we checked several state-of-the-art neural language models. As a training and testing data, we use tens of thousands of legal cases as question-opinion pairs. Text data has been subjected to advanced pre-processing adapted to the specifics of the legal domain. We empirically chose the BERT-based HerBERT model to perform...
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Simulation Environment in Python for Ship Encounter Situations
PublikacjaTo assess the risk of collision in radar navigation distance-based safety measures such as Distance at the Closest Point of Approach and Time to the Closest Point of Approach are most commonly used. Also Bow Crossing Range and Bow Crossing Time measures are good complement to the picture of the meeting situation. When ship safety domain is considered then Degree of Domain Violation and Time to Domain Violation can be applied. This...
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The Idea of a Student Research Project as a Method of Preparing a Student for Professional and Scientific Work
PublikacjaIn the paper we present the idea and implementation of a student research project course within the master’s program at the Faculty of Electronics, Telecommunications and Informatics, Gdansk Tech. It aims at preparing students for performing research and scientific tasks in future professional work. We outline the evolution from group projects into research project and the current deployment of both at bachelor’s and master’s levels...
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UNRES-GPU for Physics-Based Coarse-Grained Simulations of Protein Systems at Biological Time- and Size-Scales
PublikacjaThe dynamics of the virus like particles (VLPs) corresponding to the GII.4 Houston, GII.2 SMV, and GI.1 Norwalk strains of human noroviruses (HuNoV) that cause gastroenteritis was investigated by means of long-time (about 30 μs in the laboratory timescale) molecular dynamics simulations with the coarse-grained UNRES force field. The main motion of VLP units turned out to be the bending at the junction between the P1 subdomain (that...
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublikacjaThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
Rok 2022
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Active Learning Based on Crowdsourced Data
PublikacjaThe paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase...
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Algorytm mrówkowy do zarządzania zasobami sprzętowymi chmury obliczeniowej w przypadku różnych kategorii usług
PublikacjaZarządzanie chmurą obliczeniową odbywa się na dwóch poziomach: zarządzanie żądaniami klientów chmury oraz zarządzanie jej infrastrukturą, na której te usługi są realizowane. Analizując standardy dotyczące zarządzania usługami, w niniejszym rozdziale skoncentrowano się na drugim poziomie zarządzania, którego głównym celem jest efektywne wykonanie wskazanej usługi (lub usług) na dostępnych zasobach sprzętowych, tak by spełnione zostały...
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Architecture Design of a Networked Music Performance Platform for a Chamber Choir
PublikacjaThis paper describes an architecture design process for Networked Music Performance (NMP) platform for medium-sized conducted music ensembles, based on remote rehearsals of Academic Choir of Gdańsk University of Technology. The issues of real-time remote communication, in-person music performance, and NMP are described. Three iterative steps defining and extending the architecture of the NMP platform with additional features to...
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Architektury klasyfikatorów obrazów
PublikacjaKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
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Badanie wpływu przydziału rdzeni procesora na wydajność w środowisku skonteneryzowanym oparte na wybranym serwerze warstawy pośredniej w IoT - obserwacje i rekomendacje
PublikacjaInternet Rzeczy cieszy się coraz większym zainteresowaniem. Za- gadnienie to jest szeroko omawiane zarówno w środowisku nauko- wym, jak i w przemyśle. Ze względu na jego wielowymiarowość jest wiele aspektów, które wymagają zbadania i obserwacji. Jednym z nich jest efektywne wdrożenie i uruchomienie aplikacji w kontekście wykorzystania zasobów sprzętowych. Innym, równie istotnym, za- gadnieniem jest konteneryzacja platform IoT....
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Comparison of image pre-processing methods in liver segmentation task
PublikacjaAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublikacjaImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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DEPO: A dynamic energy‐performance optimizer tool for automatic power capping for energy efficient high‐performance computing
PublikacjaIn the article we propose an automatic power capping software tool DEPO that allows one to perform runtime optimization of performance and energy related metrics. For an assumed application model with an initialization phase followed by a running phase with uniform compute and memory intensity, the tool performs automatic tuning engaging one of the two exploration algorithms—linear search (LS) and golden section search (GSS), finds...
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Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
PublikacjaHoneybees plays vital role for the environmental sustainability and overall agricultural economy. Assisting bee colonies within their proper functioning brings the attention of researchers around the world. Electronics systems and machine learning algorithms are being developed for classifying specific undesirable bee behaviors in order to alert about upcoming substantial losses. However, classifiers could be impaired when used...
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Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs
PublikacjaIn the paper we investigate the problem of food classification from images, for the Food-101 dataset extended with 31 additional food classes from Polish cuisine. We adopted transfer learning and firstly measured training times for models such as MobileNet, MobileNetV2, ResNet50, ResNet50V2, ResNet101, ResNet101V2, InceptionV3, InceptionResNetV2, Xception, NasNetMobile and DenseNet, for systems with NVIDIA Tesla V100 (Volta) and...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublikacjaIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Greencoin – educational information system for ecoinclusion and empowering urban adaptability.
PublikacjaThe SARS-CoV19 pandemic exposed a broad spectrum of challenges for modern cities, societies and the environment at large. The post-Covid transformation requires new social, ecological and educational solutions, adjusted to modern challenges, but also equipped with technological advances that allow for digital inclusion and sustainable urban development to benefit the local economy and society. Many information systems designed...
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How to Sort Them? A Network for LEGO Bricks Classification
PublikacjaLEGO bricks are highly popular due to the ability to build almost any type of creation. This is possible thanks to availability of multiple shapes and colors of the bricks. For the smooth build process the bricks need to properly sorted and arranged. In our work we aim at creating an automated LEGO bricks sorter. With over 3700 different LEGO parts bricks classification has to be done with deep neural networks. The question arises...
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Inteligentne zarządzanie usługami chmurowymi
PublikacjaRozwój chmur obliczeniowych stanowi wyzwanie dla nowych efektywnych metod zarządzania zasobami chmurowymi, zwłaszcza, że oprócz usług typu SaaS rozwija się nowe kategorie usług jak obliczenia brzegowe czy wielochmurowe. W pracy zaproponowano ogólny model zarządzania usługami oraz efektywne procedury alokacji zasobów. Podkreślono potrzebę oszacowania parametrów zasobów chmury by zapewnić wykonanie żądanych usług. Przedstawiono również...
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Investigation of Performance and Configuration of a Selected IoT System—Middleware Deployment Benchmarking and Recommendations
PublikacjaNowadays Internet of Things is gaining more and more focus all over the world. As a concept it gives many opportunities for applications for society and it is expected that the number of software services deployed in this area will still grow fast. Especially important in this context are properties connected with deployment such as portability, scalability and balance between software requirements and hardware capabilities. In...
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Metody ekstrakcji ustrukturalizowanej treści z Wikipedii
PublikacjaWikipedia jest od dawna przedmiotem zainteresowania badaczy. Jednym z obszarów zainteresowania jest pozyskiwanie wiedzy z treści Wikipedii a to wymaga parsowania tekstu artykułów. W tym rozdziale przedstawiono analizę porównawczą różnych możliwości parsowania treści Wikipedii, wskazując problemy, z jakimi muszą się mierzyć autorzy parserów. Dzięki temu można zrozumieć, dlaczego proces wydobywania wiedzy z Wikipedii jest trudny
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Performance Assessment of Using Docker for Selected MPI Applications in a Parallel Environment Based on Commodity Hardware
PublikacjaIn the paper, we perform detailed performance analysis of three parallel MPI applications run in a parallel environment based on commodity hardware, using Docker and bare-metal configurations. The testbed applications are representative of the most typical parallel processing paradigms: master–slave, geometric Single Program Multiple Data (SPMD) as well as divide-and-conquer and feature characteristic computational and communication...
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Privacy-Preserving, Scalable Blockchain-Based Solution for Monitoring Industrial Infrastructure in the Near Real-Time
PublikacjaThis paper proposes an improved monitoring and measuring system dedicated to industrial infrastructure. Our model achieves security of data by incorporating cryptographical methods and near real-time access by the use of virtual tree structure over records. The currently available blockchain networks are not very well adapted to tasks related to the continuous monitoring of the parameters of industrial installations. In the database...
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Segmentacja obrazów medycznych przy ograniczonej liczbie adnotacji
PublikacjaW dziedzinie badań klinicznych i opieki zdrowotnej tradycyjne podejście w uczeniu głębokim polegające na wykorzystaniu dużych zbiorów danych jest trudne w realizacji. Przyczyną takiego stanu rzeczy są koszty znakowania obrazów medycznych, zwłaszcza w przypadku segmentacji obrazów medycznych. Jest to żmudna operacja, która zazwyczaj wymaga intensywnego znakowania pikseli wykonanego przez ekspertów – lekarzy. W tym rozdziale zaprezentowano...
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Semantyczne wektory słów
PublikacjaNiniejszy rozdział stanowi wstęp do rozległego zagadnienia, jakim są semantyczne wektory słów. W szczególności skupiono się w niej na metodach automatycznego tworzenia tego typu reprezentacji na podstawie dużych zbiorów danych. Omówiono także różne możliwe interpretacje tego, czym tak naprawdę jest podobieństwo słów, oraz przedstawiono wybrane zastosowania tego typu modeli.
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Synchronizacja wiedzy w systemach agentowych
PublikacjaAgenty inteligentne są jednym z komponentów stosowanych w pro- jektowaniu rozproszonych inteligentnych systemów obliczeniowych. W rozdziale wskazano istotne aspekty systemów agentowych, a na- stępnie omówiono wybrane metody synchronizacji wiedzy między agentami będącymi częścią systemu agentowego. Omówiono podej- ście właściwe dla agentów zaufanych oraz jego modyfikację dla agen- tów, które mogą celowo próbować wprowadzać inne...
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Video of LEGO Bricks on Conveyor Belt Dataset Series
PublikacjaThe dataset series titled Video of LEGO bricks on conveyor belt is composed of 14 datasets containing video recordings of a moving white conveyor belt. The recordings were created using a smartphone camera in Full HD resolution. The dataset allows for the preparation of data for neural network training, and building of a LEGO sorting machine that can help builders to organise their collections.
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What Skills for Multi-Partner Open Innovation Projects? Open Innovation Competence Profile in a Cluster Ecosystem Context
PublikacjaIndustry 4.0 and the turbulent environment have rendered increasing interest in open inno- vation that extends from the bilateral transmission of expertise to multilateral platform collaborations. Open innovation ventures are seen as intricate collaborations that require the commitment of numer- ous partners during the lifetime of the project. In order to examine the specific competence of open innovation teams, we set the research...
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Wydobywanie wiedzy z Wikipedii
PublikacjaWikipedia jest olbrzymim źródłem wiedzy encyklopedycznej gromadzonej przez ludzi i przeznaczonej dla ludzi. W systemach informatycznych odpowiednikiem takiego źródła wiedzy są ontologie. Ten rozdział pokazuje, w jaki sposób Wikipedia jest transformowana w ontologię i jak wydobywać z niej pojęcia, ich właściwości i relacje między nimi.
Rok 2021
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ANFIS-Based NPC Population Control in Video Games
PublikacjaModern computer games aim at providing rich, vivid worlds. The aim is to encourage the player to explore and interact with the in-game world. To describe the complex relations between in-game NPCs and their surrounding fuzzy logic is used. The paper presents ANFIS based population control in the video game. We present an approach allowing stabilizing the number of NPCs in-game by providing a certain amount of food to the environment....
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Assessment of OpenMP Master–Slave Implementations for Selected Irregular Parallel Applications
PublikacjaThe paper investigates various implementations of a master–slave paradigm using the popular OpenMP API and relative performance of the former using modern multi-core workstation CPUs. It is assumed that a master partitions available input into a batch of predefined number of data chunks which are then processed in parallel by a set of slaves and the procedure is repeated until all input data has been processed. The paper experimentally...
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Assessment of particular abdominal aorta section extraction from contrast-enhanced computed tomography angiography
PublikacjaThe aim of this work is to improve the accuracy of extraction of a particular abdominal aorta section and to reduce the distortion in three-dimensional Computed Tomography Angiography (CTA) images. Imaging modality and quality plays crucial role in the medical diagnostic process, thus ensuring high quality of images is essential at every stage of acquisition and processing.Noise is defined as a disturbance of the image quality...
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Benchmarking Scalability and Security Configuration Impact for A Distributed Sensors-Server IOT Use Case
PublikacjaInternet of Things has been getting more and more attention and found numerous practical applications. Especially important in this context are performance, security and ability to cope with failures. Especially crucial is to find good trade-off between these. In this article we present results of practical tests with multiple clients representing sensors sending notifications to an IoT middleware – DeviceHive. We investigate performance...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Blockchain technologies to address smart city and society challenges
PublikacjaNew Information and Communications Technologies (ICT) are changing the way in which the world works. These technologies provide new tools to face the issues of contemporary society (poverty, migrations, sustainable development challenges, governance, etc.). Among them, blockchain emerge as a disruptive technology able to make things in a completely different and innovative way. They can provide solutions where before there were...
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Buzz-based honeybee colony fingerprint
PublikacjaNon-intrusive remote monitoring has its applications in a variety of areas. For industrial surveillance case, devices are capable of detecting anomalies that may threaten machine operation. Similarly, agricultural monitoring devices are used to supervise livestock or provide higher yields. Modern IoT devices are often coupled with Machine Learning models, which provide valuable insights into device operation. However, the data...
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Embedded Representations of Wikipedia Categories
PublikacjaIn this paper, we present an approach to building neural representations of the Wikipedia category graph. We test four different methods and examine the neural embeddings in terms of preservation of graphs edges, neighborhood coverage in representation space, and their influence on the results of a task predicting parent of two categories. The main contribution of this paper is application of neural representations for improving the...
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Fast Approximate String Search for Wikification
PublikacjaThe paper presents a novel method for fast approximate string search based on neural distance metrics embeddings. Our research is focused primarily on applying the proposed method for entity retrieval in the Wikification process, which is similar to edit distance-based similarity search on the typical dictionary. The proposed method has been compared with symmetric delete spelling correction algorithm and proven to be more efficient...
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Generowanie tekstu z użyciem sieci typu Transformer
PublikacjaOpisano działanie wybranych modeli uczenia maszynowego znajdujących zastosowanie w przetwarzaniu języka naturalnego w szczególności wy- korzystywanych do generowania tekstu. Przedstawiono również model BERT i jego różne wersje, a także praktyczne wykorzystanie modeli typu Transformer. Przedstawiono ich działanie w aplikacji zmieniającej nastrój tekstu w sposób sekwencyjny.
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Hierarchical 2-step neural-based LEGO bricks detection and labeling
PublikacjaLEGO bricks are extremely popular and allow the creation of almost any type of construction due to multiple shapes available. LEGO building requires however proper brick arrangement, usually done by shape. With over 3700 different LEGO parts this can be troublesome. In this paper, we propose a solution for object detection and annotation on images. The solution is designed as a part of an automated LEGO bricks arrangement. The...
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Human awareness versus Autonomous Vehicles view: comparison of reaction times during emergencies
PublikacjaHuman safety is one of the most critical factors when a new technology is introduced to the everyday use. It was no different in the case of Autonomous Vehicles (AV), designed to replace generally available Conventional Vehicles (CV) in the future. AV rules, from the start, focus on guaranteeing safety for passengers and other road users, and these assumptions usually work during normal traffic conditions. However, there is still...
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Implementacja wykrywalnych usług typu REST na platformie Jakarta EE
PublikacjaNiniejszy rozdział przedstawia propozycję w jaki sposób może być realizowana implementacja wykrywalnych usług sieciowych opartych na stylu architektonicznym REST na platformie Jakarta EE. Zostały tutaj przedstawione zarówno podstawy teoretyczne niezależne od zastosowanej platformy technologicznej, jak i szczegóły implementacji w technologii JAX-RS wchodzącej w skład platformy Jakarta EE. W szczególności zostały tutaj przedstawione...
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Jak wykraść złoto smokowi? - uczenie ze wzmocnieniem w świecie Wumpusa
PublikacjaNiniejszy rozdział zawiera łagodne wprowadzenie do problematyki uczenia ze wzmocnieniem, w którym podstawy teoretyczne wyjaśniane są na przykładzie przewodnim, jakim jest zagadnienie nauczenia agenta poruszania się w świecie potwora o imieniu Wumpus (ang. Wumpus world), klasycznym środowisku do testowania logicznego rozumowania agentów (problem nietrywialny dla algorytmów uczenia ze wzmocnieniem). Przedstawiona jest główna idea...
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Klasyfikacja aktywności kory wzrokowej za pomocą elektroencefalografu
PublikacjaW niniejszej pracy została przedstawiona metodologia konstrukcji i oceny systemu cyfrowego automatycznie klasyfikującego dane pochodzące z elektroencefalografu. Opracowana procedura badawcza pozwoliła na przetestowanie rozwiązania na różnych osobach, w różnym wieku, o różnych porach dnia, z wykorzystaniem różnych konfiguracji urządzeń i modeli zjawiska. Uzyskano stuprocentową skuteczność automatycznego rozpoznania stanu spoczynkowego...
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Klasyfikacja tekstu przy użyciu grafowych sieci neuronowych
PublikacjaWspółczesnym algorytmom analizy tekstu wciąż daleko do ludzkiego poziomu jego zrozumienia. Jednym z wyzwań jest znajdowanie przez maszynę związków pomiędzy odległymi fragmentami tekstu. Próbą rozwiązania tego problemu są grafowe reprezentacje tekstu, które bardzo dobrze sprawdzają się w przedstawianiu złożonych zależności. W tekście opisane zostały dwie metody grafowej reprezentacji tekstu oraz algorytm grafowych konwolucyjnych...
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Licencjonowanie oprogramowania
PublikacjaWolne i otwarte oprogramowanie przeżywa ostatnimi laty rozkwit. Co raz więcej przedsiębiorstw komercyjnych opiera rozwój swoich firm na otwartym oprogramowaniu. Zarówno mali, jak i duzi gracze mają świadomość komplikacji współczesnych systemów i niemożności samodzielnego ich rozwoju. Z pomocą przychodzi otwarte podejście do wytwarzania oprogramowania. Wymaga to jednak pewnego zrozumienia uwarunkowań prawnych, a w szczególności...
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Multi-Aspect Quality Assessment Of Mobile Image Classifiers For Companion Applications In The Publishing Sector
PublikacjaThe paper presents the problem of quality assessment of image classifiers used in mobile phones for complimentary companion applications. The advantages of using this kind of applications have been described and a Narrator on Demand (NoD) functionality has been described as one of the examples, where the application plays an audio file related to a book page that is physically in front of the phone's camera. For such a NoD application,...
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Multi-objective Tabu-based Differential Evolution for Teleportation of Smart Virtual Machines in Private Computing Clouds
PublikacjaWe propose a multi-objective approach for using differential evolution algorithm with tabu search algorithm as an additional mutation for live migration (teleportation) of virtual machines. This issue is crucial in private computing clouds. Teleportation of virtual machines is supposed to be planned to determine Pareto-optimal solutions for several criteria such as workload of the bottleneck host, communication capacity of the...
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Najczęstsze problemy usługowych środowisk wdrożeniowych
PublikacjaZakres dostępnych obecnie rozwiązań informatycznych umożliwia zna- czące usprawnienie procesu wytwarzania i dostarczania oprogramowania do klienta. Poprawna integracja środowiska wytwórczego pozwala wy- eliminować szereg problemów dotyczących wewnętrznej współpracy ze- społów developerskich. Zmiana architektur aplikacji z monolitycznych na rozproszone heterogeniczne zbiory usług wymaga innego podejścia do wdrażania usług. Dotychczasowe...
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Neuronowe modele z atencją w przetwarzaniu języka naturalnego
PublikacjaCelem niniejszego rozdziału jest wprowadzenie w tematykę sieci neuronowych z atencją oraz ich zastosowań w przetwarzaniu języka naturalnego. Rozdział skupia się w szczególności na dokładnym omówieniu architektury modelu Transformer, wykorzystującego atencję jako podstawowy mechanizm swojego działania.
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Offshore benthic habitat mapping based on object-based image analysis and geomorphometric approach. A case study from the Slupsk Bank, Southern Baltic Sea
PublikacjaBenthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to...
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Optimization of Data Assignment for Parallel Processing in a Hybrid Heterogeneous Environment Using Integer Linear Programming
PublikacjaIn the paper we investigate a practical approach to application of integer linear programming for optimization of data assignment to compute units in a multi-level heterogeneous environment with various compute devices, including CPUs, GPUs and Intel Xeon Phis. The model considers an application that processes a large number of data chunks in parallel on various compute units and takes into account computations, communication including...
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Paradoks decyzyjny – racjonalne i intuicyjne podejmowanie decyzji
PublikacjaW pracy scharakteryzowano poszczególne etapy działań prowadzące do znajdowania najlepszych rozwiązań dla rozpatrywanego problemu. Zwrócono uwagę na paradoks decyzyjny który wskazuje, że mądre rozwiązanie problemu wymaga zarówno racjonalnego, jak i intuicyjnego podejścia. Na przykładzie sortowania obrazów zaprezentowano niezależnie oba podejścia podkreślając potrzebę ich wzajemnego uzupełniania się. Podkreślono trudność budowy algorytmów,...
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Problemy jakości w metodach Agile
PublikacjaZwinne metody wytwarzania osiągnęły w zawrotnym tempie niebywały sukces. Według różnych doniesień od 50 do 70% firm IT stosuje metody zwinne na stałe lub okazjonalnie . Jednak znaczna część firm stosuje wybiórczo praktyki zalecane przez Agile . Jakie to praktyki? Jakie problemy występują przy ich stosowaniu i jak firmy radzą sobie z tymi problemami? Jak wpływają na jakość wytwarzanego oprogramowania? Jakie są warunki krytyczne...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublikacjaThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Reprezentacja danych dźwiękowych w kontekście metod uczenia maszynowego
PublikacjaDźwięk odgrywa kluczową rolę w przekazywaniu informacji lub ostrzeganiu o niebezpieczeństwie. Do opracowania wydajnego cyfrowego asystenta głosowego zdolnego do efektywnej współpracy z człowiekiem niezbędne jest użycie algorytmów opisujących sygnał dźwiękowy w formie cyfrowej. W poniższej pracy skategoryzowano i opisano najpowszechniejsze metody opisu sygnałów audio używanych jako wejścia dla algorytmów uczenia maszynowego. Wskazano...
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Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublikacjaDeployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the...
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Semantic segmentation training using imperfect annotations and loss masking
PublikacjaOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublikacjaTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublikacjaTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Towards Scalable Simulation of Federated Learning
PublikacjaFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...
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Wzajemne wykluczanie w programowaniu współbieżnym
PublikacjaW rozdziale opisano wzajemne wykluczanie wątków w programach współbieżnych. Przedstawiono zarówno podejście proceduralne (semafory), jak i obiektowe (monitory). Omówiono sposoby działania obu mechanizmów synchronizacji oraz różnice pomiędzy nimi. Sposoby użycia omawianych mechanizmów zostały zilustrowane wzorcami: wzajemnego wykluczania oraz producent–konsument.
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Zjawisko wyścigu w programowaniu współbieżnym
PublikacjaW rozdziale przedstawiono omówienie podstawowego problemu, z jakim, prędzej czy później, styka się każdy programista piszący oprogramowanie wykorzystujące współbieżność. W praktyce będzie to każdy programista starający się w pełni wykorzystywać moc obliczeniową współczesnych wielordzeniowych procesorów i akceleratorów
Rok 2020
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublikacjaOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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Automated Classifier Development Process for Recognizing Book Pages from Video Frames
PublikacjaOne of the latest developments made by publishing companies is introducing mixed and augmented reality to their printed media (e.g. to produce augmented books). An important computer vision problem that they are facing is classification of book pages from video frames. The problem is non-trivial, especially considering that typical training data is limited to only one digital original per book page, while the trained classifier...