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Wyniki wyszukiwania dla: deblurring, denoising, multi-task learning, video enhancement
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Justyna Szostak dr inż.
OsobyI Gdańsk University of Technology: Chair of the Rector’s Internationalization Committee (October 2020 - Present) Erasmus + Coordinator for students and staff members, Faculty of Applied Physics and Mathematics (Mar 2017 - Present) Dean's Proxy for Internationalization, Faculty of Applied Physics and Mathematics (October 2020 - Present) Coordinator of the International Relations Office of the Faculty of Applied Physics and...
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Classification of Sea Going Vessels Properties Using SAR Satellite Images
PublikacjaThe aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...
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SegSperm - a dataset of sperm images for blurry and small object segmentation
Dane BadawczeMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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Multi-Decision Analysis for selection of the best procedure for PAHs determination in smoked food.
PublikacjaMaking a proper decision in multifacitated situation is very challenging task. Especially, if there are many alternatives and criteria, even contradictory ones. The support tools may be application of MultiCriteria Decision Analysis methods. In this study the application of PROMETHEE...
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Weakly-Supervised Word-Level Pronunciation Error Detection in Non-Native English Speech
PublikacjaWe propose a weakly-supervised model for word-level mispronunciation detection in non-native (L2) English speech. To train this model, phonetically transcribed L2 speech is not required and we only need to mark mispronounced words. The lack of phonetic transcriptions for L2 speech means that the model has to learn only from a weak signal of word-level mispronunciations. Because of that and due to the limited amount of mispronounced...
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Implementation of multi-operand addition in FPGA using high-level synthesis
PublikacjaThe paper presents the results of high-level synthesis (HLS) of multi-operand adders in FPGA using the Vivado Xilinx environment. The aim was to estimate the hardware amount and latency of adders described in C-code. The main task of the presented experiments was to compare the implementations of the carry-save adder (CSA) type multi-operand adders obtained as the effect of the HLS synthesis and those based on the basic component...
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Design of a microrobotic wrist for needle laparoscopic surgery
PublikacjaThe paper addresses the design of a micro wrist for needle laparoscopic surgery (needlescopy) using MEMS technology and an original 3 degree of freedom, 3D architecture. Advancement in needlescopy drives the development of multi-dof micro-tools 1-2mmin diameter with 3D mobility but standard available fabricationtechniques are for 2.5D structures. The paper discusses thedevelopment steps and design solutions for the realization...
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From Sequential to Parallel Implementation of NLP Using the Actor Model
PublikacjaThe article focuses on presenting methods allowing easy parallelization of an existing, sequential Natural Language Processing (NLP) application within a multi-core system. The actor-based solution implemented with the Akka framework has been applied and compared to an application based on Task Parallel Library (TPL) and to the original sequential application. Architectures, data and control flows are described along with execution...
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Experimental study on single phase operation of microjet augmented heat exchanger with enhanced heat transfer surface
PublikacjaThe article presents experimental investigations on a prototype heat exchanger. Presented research is focused on combined active and passive enhancement techniques of surface modification and microjet impingement. The results were compared to reference plate heat exchanger without microjet impingement. The Wilson plot method was applied to determine the heat transfer coefficients in the single phase operation. The heat exchanger...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Cross-domain applications of multimodal human-computer interfaces
PublikacjaDeveloped multimodal interfaces for education applications and for disabled people are presented, including interactive electronic whiteboard based on video image analysis, application for controlling computers with mouth gestures and audio interface for speech stretching for hearing impaired and stuttering people and intelligent pen allowing for diagnosing and ameliorating developmental dyslexia. The eye-gaze tracking system named...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?
PublikacjaIn this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning...
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Maritime traffic situation awareness analysis via high-fidelity ship imaging trajectory
PublikacjaSituation awareness provides crucial yet instant information to maritime traffic participants, and significant attentions are paid to implement traffic situation awareness task via various maritime data source (e.g., automatic identification system, maritime surveillance video, radar, etc.). The study aims to analyze traffic situation with the support of ship imaging trajectory. First, we employ the dark channel prior model to...
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A new multi-process collaborative architecture for time series classification
PublikacjaTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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AITP - AI Thermal Pedestrians Dataset
PublikacjaEfficient pedestrian detection is a very important task in ensuring safety within road conditions, especially after sunset. One way to achieve this goal is to use thermal imaging in conjunction with deep learning methods and an annotated dataset for models training. In this work, such a dataset has been created by capturing thermal images of pedestrians in different weather and traffic conditions. All images were manually annotated...
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Rapid Multi-Criterial Antenna Optimization by Means of Pareto Front Triangulation and Interpolative Design Predictors
PublikacjaModern antenna systems are designed to meet stringent performance requirements pertinent to both their electrical and field properties. The objectives typically stay in conflict with each other. As the simultaneous improvement of all performance parameters is rarely possible, compromise solutions have to be sought. The most comprehensive information about available design trade-offs can be obtained through multi-objective optimization...
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A Generative Approach to Hull Design for a Small Watercraft
PublikacjaIn the field of ocean engineering, the task of spatial hull modelling is one of the most complicated problems in ship design. This study presents a procedure applied as a generative approach to the design problems for the hull geometry of small vessels using elements of concurrent design with multi-criteria optimisation processes. Based upon widely available commercial software, an algorithm for the mathematical formulation of...
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DevEmo—Software Developers’ Facial Expression Dataset
PublikacjaThe COVID-19 pandemic has increased the relevance of remote activities and digital tools for education, work, and other aspects of daily life. This reality has highlighted the need for emotion recognition technology to better understand the emotions of computer users and provide support in remote environments. Emotion recognition can play a critical role in improving the remote experience and ensuring that individuals are able...
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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Study on Strategy in University Laboratory Class Teaching
PublikacjaLaboratory teaching is a critical way to ensure the effective input of techniques in engineering learning. Laboratory teaching not only contributes to improving course quality but also helps enrich comprehensive engineering application ability. However, there are some typical problems in current university laboratory teaching, such as rigid and isolated course design, outdated contents and materials, and not encouraging innovation...
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublikacjaW pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...
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Muhammad Usman PhD
OsobyMuhammad Usman is a researcher at the Gdansk University of Technology, currently working on the BE-Light project focused on face skin analysis using multimodal imaging and machine learning methods. He previously worked as a Hardware Test Engineer at Apple Inc., specializing in the rigorous testing and validation of electronic systems, ensuring reliability and performance. He holds a Master of Science in Automation and Control from...
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Voice command recognition using hybrid genetic algorithm
PublikacjaAbstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...
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Dysfunctional prefrontal cortical network activity and interactions following cannabinoid receptor activation.
PublikacjaCoordinated activity spanning anatomically distributed neuronal networks underpins cognition and mediates limbic-cortical interactions during learning, memory, and decision-making. We used CP55940, a potent agonist of brain cannabinoid receptors known to disrupt coordinated activity in hippocampus, to investigate the roles of network oscillations during hippocampal and medial prefrontal cortical (mPFC) interactions in rats. During...
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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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Constrained multi-objective optimization of compact microwave circuits by design triangulation and pareto front interpolation
PublikacjaDevelopment of microwave components is an inherently multi-objective task. This is especially pertinent to the design closure stage, i.e., final adjustment of geometry and/or material parameters carried out to improve the electrical performance of the system. The design goals are often conflicting so that the improvement of one normally leads to a degradation of others. Compact microwave passives constitute a representative case:...
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Visual Content Representation for Cognitive Systems: Towards Augmented Intelligence
PublikacjaCognitive Vision Systems have gained significant attention from academia and industry during the past few decades. One of the main reasons behind this interest is the potential of such technologies to revolutionize human life since they intend to work robustly under complex visual scenes (which environmental conditions may vary), adapting to a comprehensive range of unforeseen changes, and exhibiting prospective behavior. The combination...
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The Application of Vibration Recording and Analysis in Tribological Research on Sliding Friction
PublikacjaThe paper reports on a tribological research on the macroscopic manifestation and characteristics of sliding friction. The aim of the task was to measure friction in lubricated sliding contacts and test the interactions between the environment (the test rig) and the experimental friction contact. Friction-induced vibrations were observed and studied as a manifestation of the process. The typical set of velocity and force/torque...
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Approximate and analytic flow models for leak detection and identification
PublikacjaThe article presents a comprehensive quantitative comparison of four analytical models that, in different ways, describe the flow process in transmission pipelines necessary in the task of detecting and isolating leaks. First, the analyzed models are briefly presented. Then, a novel model comparison framework was introduced along with a methodology for generating data and assessing diagnostic effectiveness. The study presents basic...
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Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models
PublikacjaMulti-objective optimization of antenna structures is a challenging task due to high-computational cost of evaluating the design objectives as well as large number of adjustable parameters. Design speedup can be achieved by means of surrogate-based optimization techniques. In particular, a combination of variable-fidelity electromagnetic (EM) simulations, design space reduction techniques, response surface approximation (RSA) models,...
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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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Low-cost multi-objective optimization and experimental validation of UWB MIMO antenna
PublikacjaPurpose–The purpose of this paper is to validate methodologies for expedited multi-objective designoptimization of complex antenna structures both numerically and experimentally.Design/methodology/approach–The task of identifying the best possible trade-offs between theantenna size and its electrical performance is formulated as multi-objective optimization problem.Algorithmic frameworks are described for finding Pareto-optimal...
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Fluid–Structure Interaction methods for the progressive anatomical and artificial aortic valve stenosis
PublikacjaCardiovascular system diseases, as aortic valve stenosis, are the main cause of mortality and morbidity among patients. There is still a room for enhancement of the diagnostic and therapeutic procedures, which will lead to improvement of the treatment. One of the remedies are the computer tools to support the medical diagnoses and prostheses design. The development of a procedure for modeling the aortic valves: anatomical tricuspid...
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How to Design Affect-aware Educational Systems – the AFFINT Process Approach
PublikacjaComputer systems, that support learning processes, can adapt to the needs and states of a learner. The adaptation might directly address the knowledge deficits and most tutoring systems apply an adaptable learning path of that kind. Apart from a preliminary knowledge state, there are more factors, that influence education effectiveness and among those there are fluctuating emotional states. The tutoring systems may recognize or...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublikacjaWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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Deep Features Class Activation Map for Thermal Face Detection and Tracking
PublikacjaRecently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...
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Global Miniaturization of Broadband Antennas by Prescreening and Machine Learning
PublikacjaThe development of contemporary electronic components, particularly antennas, places significant emphasis on miniaturization. This trend is driven by the emergence of technologies such as mobile communications, the internet of things, radio-frequency identification, and implantable devices. The need for small size is accompanied by heightened demands on electrical and field properties, posing a considerable challenge for antenna...
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Rapid multi-objective optimization of antennas using nested kriging surrogates and single-fidelity EM simulation models
PublikacjaEver increasing performance requirements make the design of contemporary antenna systems a complex and multi-stage process. One of the challenges, pertinent to the emerging application areas but also some of the recent trends (miniaturization, demands for multi-functionality, etc.), is the necessity of handling several performance figures such as impedance matching, gain, or axial ratio, often over multiple frequency bands. The...
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Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth
PublikacjaAs healthcare costs continue to rise, finding affordable and non-invasive ways to monitor vital signs is increasingly important. One of the key metrics for assessing overall health and identifying potential issues early on is respiratory rate (RR). Most of the existing methods require multiple steps that consist of image and signal processing. This might be difficult to deploy on edge devices that often do not have specialized...
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Comparison of Deep Learning Approaches in Classification of Glacial Landforms
PublikacjaGlacial landforms, created by the continuous movements of glaciers over millennia, are crucial topics in geomorphological research. Their systematic analysis affords invaluable insights into past climatic oscillations and augments understanding of long-term climate change dynamics. The classification of these types of terrain traditionally depends on labor-intensive manual or semi-automated methods. However, the emergence of automated...
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublikacjaThis paper presents two methods of training complexity reduction by additional selection of features to check in object detector training task by AdaBoost training algorithm. In the first method, the features with weak performance at first weak classifier building process are reduced based on a list of features sorted by minimum weighted error. In the second method the feature similarity measures are used to throw away that features...
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Quantitative risk assessment of new ship designs in damage conditions
PublikacjaThe paper is devoted to safety of ships in damage conditions. The novel contribution of the paper is connected with a new Multi-Task ship (MT-ship) design at the preliminary stage of design. There are a few problems at the preliminary stage that should be considered. One problem is connected with if the quantitative risk-based method is a reliable and formal method for safety assessment of such the new design (MT-ship) in damage...
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The principles of arturbain.fr for teaching sustainable urban design
PublikacjaThe article is an attempt to show how important it is in the contemporary education of architecture students to use an ordered repertoire of principles and concepts of a universal nature, at the same time, pointing to the new directions of solutions and answers to the problems of the 21st century. This task is implemented by the French Association L'Arturbain dans les Territoires. It is accompanied by an idea consisting in observing...
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Advanced Ship Control Methods
PublikacjaThe chapter presents two main streams of research in vessel control at sea: dynamic positioning (DP) of the vessel and decision support in case of collision at sea. The control structure and basic requirements for the DP system are defined. Selected issues of automatic control of a dynamically positioned vessel are discussed. A review of advanced methods of controlling a DP ship is carried out, taking into account the tasks of...
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Teaching High–performance Computing Systems – A Case Study with Parallel Programming APIs: MPI, OpenMP and CUDA
PublikacjaHigh performance computing (HPC) education has become essential in recent years, especially that parallel computing on high performance computing systems enables modern machine learning models to grow in scale. This significant increase in the computational power of modern supercomputers relies on a large number of cores in modern CPUs and GPUs. As a consequence, parallel program development based on parallel thinking has become...
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CAD. Integrated Architectural Design, MSc Arch (2023/24)
Kursy OnlineDetailed understanding of optimizing the design process using parametric BIM (Building Information Modeling) in the Autodesk Revit Architecture program. Practical design exercises included familiarize students with methods of integrating parametric design and exchanging data with other CAD/BIM programs, modifying parametric objects and generating automatic 2D/3D architectural documentation. The lesson plan introduces students to...
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Effect of multi-walled carbon nanotubes properties on the photocatalytic activity of bismuth-based composites synthesised via an imidazolium ionic liquid
PublikacjaThe use of various types of multi-walled carbon nanotubes in the synthesis of bismuth oxybromide semiconductors via imidazolium ionic liquid was studied in detail. The effect of the MWCNT shape, specific surface area, and various diameters on the morphology, surface properties and photoactivity of the Bi-based composites has been investigated for the first time. So far, the literature has only shown the enhancement of photocatalytic...