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- Publikacje 644 wyników po odfiltrowaniu
- Czasopisma 36 wyników po odfiltrowaniu
- Konferencje 53 wyników po odfiltrowaniu
- Osoby 35 wyników po odfiltrowaniu
- Projekty 2 wyników po odfiltrowaniu
- Kursy Online 14 wyników po odfiltrowaniu
- Wydarzenia 3 wyników po odfiltrowaniu
- Dane Badawcze 20 wyników po odfiltrowaniu
Wyniki wyszukiwania dla: deep neural networks, explainable artificial intelligence, adver-sarial attacks
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Selection of Features for Multimodal Vocalic Segments Classification
PublikacjaEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
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LSTM-based method for LOS/NLOS identification in an indoor environment
PublikacjaDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
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Adversarial attack algorithm for traffic sign recognition
PublikacjaDeep learning suffers from the threat of adversarial attacks, and its defense methods have become a research hotspot. In all applications of deep learning, intelligent driving is an important and promising one, facing serious threat of adversarial attack in the meanwhile. To address the adversarial attack, this paper takes the traffic sign recognition as a typical object, for it is the core function of intelligent driving. Considering...
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I, Robot: between angel and evil
PublikacjaThe boosting of most digital innovations within recent technology progress by artificial intelligence (AI) constitutes a growing topic of interest. Besides its technical aspects, increasing research activity may be observed in the domain of security challenges, and therefore of responsibility related to the controlled or hypothetically uncontrolled or autonomous emergence of AI solutions. Consequently, responsibility and ethics...
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublikacjaThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Zarządzanie zaufaniem w bezprzewodowych sieciach czujników - studium przypadku
PublikacjaW artykule przedstawiono studium przypadku dotyczące zastosowania bezprzewodowej sieci czujników do wspomagania pacjenta z nadwagą w jego środowisku domowym. Przyjęto, że sieć wykorzystuje metodę rozproszonego zarządzania zaufaniem i pokazano, że metoda ta umożliwia wykrycie i izolację czujników realizujących działania sprzeczne z polityką sieci. Ilościowe oszacowanie czasu niezbędnego do wykrycia takich...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublikacjaBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Problems of modelling toxic compounds emitted by a marine internal combustion engine in unsteady states
PublikacjaContemporary engine tests are performed based on the theory of experiment. The available versions of programmes used for analysing experimental data make frequent use of the multiple regression model, which enables examining effects and interactions between input model parameters and a single output variable. The use of multi-equation models provides more freedom in analysing the measured results, as those models enable simultaneous...
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Garnizon district in Gdansk, Poland
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Seestadt Aspern, Vienna, Austria
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Västra Hamnen, Malmö, Sweden.
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Hammarby-Sjöstad, Stockholm, Sweden.
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Pilestredet Park, Oslo, Norway.
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / King’s Cross, London, UK.
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Oceanhamnen, Helsingborg, Sweden
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / La Courrouze district in Rennes, France
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Pose classification in the gesture recognition using the linear optical sensor
PublikacjaGesture sensors for mobile devices, which have a capability of distinguishing hand poses, require efficient and accurate classifiers in order to recognize gestures based on the sequences of primitives. Two methods of poses recognition for the optical linear sensor were proposed and validated. The Gaussian distribution fitting and Artificial Neural Network based methods represent two kinds of classification approaches. Three types...
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RECODIS: Resilient Communication Services Protecting End-user Applications from Disaster-based Failures
PublikacjaDisaster-based failures can seriously disrupt any communication network, making its services unavailable. Such disruptions may be caused by natural disasters, technology-related failures, or malicious attacks, and they are observably increasing in number, intensity and scale. When network services that are a part of critical infrastructure become unavailable, commercial and/or societal problems are inevitable. The issue of limiting...
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Service-based Resilience for Embedded IoT Networks
PublikacjaEmbedded IoT networks are the backbone of safety-critical systems like smart factories, autonomous vehicles, and airplanes. Therefore, resilience against failures and attacks should be a prior concern already in their design stage. In this study, we introduce a service-based network model as an MILP optimization problem for the efficient deployment of a service overlay to the embedded network by meeting QoS and resilience requirements....
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Improving the Survivability of Carrier Networks to Large-Scale Disasters
PublikacjaThis chapter is dedicated to the description of methods aiming to improve the survivability of carrier networks to large-scale disasters. First, a disaster classification and associated risk analysis is described, and the disaster-aware submarine fibre-optic cable deployment is addressed aiming to minimize the expected costs in case of natural disasters. Then, the chapter addresses the improvement of the network connectivity resilience...
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(eng)aging! 2021 Technologie wspierające aktywność i niezależność seniorów w państwach V4
ProjektyProjekt realizowany w Katedra Inteligentnych Systemów Interaktywnych zgodnie z porozumieniem 22020301/1 z dnia 2021-01-08
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublikacjaObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Mohsan Ali Master of Science in Computer Science
OsobyMohsan Ali is a researcher at the University of the Aegean. He won the Marie-Curie Scholarship in 2021 in the field of open data ecosystem (ODECO) to pursue his PhD degree at the University of the Aegean. Currently, he is working on the technical interoperability of open data in the information systems laboratory; this position is funded by ODECO. His areas of expertise are open data, open data interoperability, data science, natural...
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Smart metering - social risk perception and risk governance (10h, 2 ECTS credits)
Kursy OnlineThe goal of the course is to broaden the understanding of technology-related risks and to present the concepts of social risk perception and risk governance in the context of smart metering technology. In current phase of technological development – known as the fourth industrial revolution – rapid and profound changes are setting up new and particularly destabilizing risks. In more and more complex technological systems that constitute...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublikacjaCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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Adaptacyjny algorytm filtracji sygnału fonokardiograficznego wykorzystujący sztuczną sieć neuronową
PublikacjaPodstawowym problemem podczas projektowania systemu autodiagnostyki chorób serca, bazującego na analizie sygnału fonokardiograficznego (PCG), jest konieczność zapewnienia, niezależnie od warunków zewnętrznych, sygnału o wysokiej jakości. W artykule, bazując na zdolności Sztucznej Sieci Neuronowej (SSN) do predykcji sygnałów periodycznych oraz quasi-periodycznych, został opracowany adaptacyjny algorytm filtracji dźwięków serca....
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Tomasz Korol dr hab. inż.
OsobyWykształcenie Politechnika Gdańska, Wydział Zarządzania i Ekonomii (2001) University of Applied Sciences Stralsund (1999) Stopień naukowy Doktor habilitowany – Politechnika Gdańska, Wydział Zarządzania i Ekonomii (2015) Doktor – Politechnika Gdańska, Wydział Zarządzania i Ekonomii (2004) Zatrudnienie Politechnika Gdańska: profesor uczelni (od 2019); profesor nadzwyczajny (2017-2019); adiunkt (2004-2016); asystent (2001-2004) I-Shou...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublikacjaThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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A note on the affective computing systems and machines: a classification and appraisal
PublikacjaAffective computing (AfC) is a continuously growing multidisciplinary field, spanning areas from artificial intelligence, throughout engineering, psychology, education, cognitive science, to sociology. Therefore, many studies have been devoted to the aim of addressing numerous issues, regarding different facets of AfC solutions. However, there is a lack of classification of the AfC systems. This study aims to fill this gap by reviewing...
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Evaluating Performance and Accuracy Improvements for Attention-OCR
PublikacjaIn this paper we evaluated a set of potential improvements to the successful Attention-OCR architecture, designed to predict multiline text from unconstrained scenes in real-world images. We investigated the impact of several optimizations on model’s accuracy, including employing dynamic RNNs (Recurrent Neural Networks), scheduled sampling, BiLSTM (Bidirectional Long Short-Term Memory) and a modified attention model. BiLSTM was...
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Collaborative Data Acquisition and Learning Support
PublikacjaWith the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...
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Development of an AI-based audiogram classification method for patient referral
PublikacjaHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
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Numerical Modelling for Prediction of Compression Index from Soil Index Properties in Jimma town, Ethiopia
PublikacjaIn this study, correlations are developed to predict compression index (Cc) from index parameters so that one can be able to model Jimma soils with compression index using simple laboratory tests. Undisturbed and disturbed soil samples from twelve different locations in Jimma town were collected. Laboratory tests like specific gravity, grain size analysis, Atterberg limit, and one-dimensional consolidation test for a total of twenty-four...
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International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
Konferencje -
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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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublikacjaFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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Interactive Decision Making, Inżynieria Środowiska, Environmental Engineering, 2023/2024 (summer semester)
Kursy OnlineThe course is designed for students of MSc Studies in Environmental Engineering (studies in Polish and English) Person responsible for the subject, carrying out lectures and tutorials: mgr inż. Agata.Siemaszko; agata.siemaszko@pg.edu.pl The person conducting the lectures and tutorials: dr inż. Anna Jakubczyk-Gałczyńska; anna.jakubczyk@pg.edu.pl The course is conducted using the Project-Based Learning (PBL) method. It provides...
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Adam Dąbrowski dr inż.
OsobyAdam Dąbrowski uzyskał stopień doktora nauk inżynieryjno-technicznych w dyscyplinie inżynieria mechaniczna na Politechnice Gdańskiej oraz ukończył studia II stopnia na kierunku mechatronika na Technische Universität Hamburg a także double degree Engineering and Management of Space Systems na Hochschule Bremen. Posiada doświadczenie przemysłowe (Instytut Lotnictwa w Warszawie, SICK AG w Hamburgu, Blue Dot Solutions w Gdańsku, Niemieckie...
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Application of ANN and PCA to two-phase flow evaluation using radioisotopes
PublikacjaIn the two-phase flow measurements a method involving the absorption of gamma radiation can be applied among others. Analysis of the signals from the scintillation probes can be used to determine the number of flow parameters and to recognize flow structure. Three types of flow regimes as plug, bubble, and transitional plug – bubble flows were considered in this work. The article shows how features of the signals in the time and...
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Łukasz Szeremeta
OsobyMoje obecne obszary badawcze to zagadnienia związane z grafami własności, cheminformatyką i Semantic Web. Interesuję się również najnowszymi zastosowaniami sztucznej inteligencji.
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Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study
PublikacjaIn this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach...
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Monitoring the gas turbine start-up phase on the platform using a hierarchical model based on Multi-Layer Perceptron networks
PublikacjaVery often, the operation of diagnostic systems is related to the evaluation of process functionality, where the diagnostics is carried out using reference models prepared on the basis of the process description in the nominal state. The main goal of the work is to develop a hierarchical gas turbine reference model for the estimation of start-up parameters based on multi-layer perceptron neural networks. A functional decomposition...
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Zastosowanie sieci neuronowych do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu
PublikacjaDetekcja impulsów w odebranym sygnale radiowym, zwłaszcza w obecności silnego szumu oraz trendu, jest trudnym zadaniem. Artykuł przedstawia propozycje rozwiązań wykorzystujących sieci neuronowe do detekcji impulsów o znanym kształcie w obecności silnego szumu i trendu. Na potrzeby realizacji tego zadania zaproponowano dwie architektury. W pracy przedstawiono wyniki badań wpływu kształtu impulsu, mocy zakłóceń szumowych oraz trendu...
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Musical Instrument Identification Using Deep Learning Approach
PublikacjaThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublikacjaPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
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Project-Based Collaborative Research and Training Roadmap for Manufacturing Based on Industry 4.0
PublikacjaThe importance of the economy being up to date with the latest developments, such as Industry 4.0, is more evident than ever before. Successful implementation of Industry 4.0 principles requires close cooperation of industry and state authorities with universities. A paradigm of such cooperation is described in this paper stemming from university partners with partly overlapping and partly complementary areas of expertise in manufacturing....
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Bio-inspired Decisional DNA in Machinas and other Man-made Systems: The Way Forward
PublikacjaArtificial bio-inspired intelligent techniques and systems supporting smart, knowledge-based solutions of real world problems which are currently researched very extensively by research teams around the world, have enormous potential to enhance automation of decision making and problem solving for a number of diverse areas including design, manufacturing, Information Technology (IT), social communities of practice, and economics...
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AUTOMATYCZNA KLASYFIKACJA MOWY PATOLOGICZNEJ
PublikacjaAplikacja przedstawiona w niniejszym rozdziale służy do automatycznego wykrywania mowy patologicznej na podstawie bazy nagrań. W pierwszej kolejności przedstawiono założenia leżące u podstaw przeprowadzonych badan wraz z wyborem bazy mowy patologicznej. Zaprezentowano również zastosowane algorytmy oraz cechy sygnału mowy, które pozwalają odróżnić mowę niezaburzoną od mowy patologicznej. Wytrenowane sieci neuronowe zostały następnie...
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Optimized Computational Intelligence Model for Estimating the Flexural Behavior of Composite Shear Walls
PublikacjaThis article presents a novel approach to estimate the flexural capacity of reinforced concrete-filled composite plate shear walls using an optimized computational intelligence model. The proposed model was developed and validated based on 47 laboratory data points and the Transit Search (TS) optimization algorithm. Using 80% of the experimental dataset, the optimized model was selected by determining the unknown coefficients of...