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Search results for: VOCATIONAL TRAINING, INNOVATIVE TRAINING MASTER BSR, ERASMUS+
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublicationW 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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Development and test of fex, a fingers extending exoskeleton for rehabilitation and regaining mobility
PublicationThis paper presents the design process of an exoskeleton for executing human fingers' extension movement for the rehabilitation procedures and as an active orthosis purposes, together with its first clinical usability tests of a robotic exoskeleton. Furthermore, the Fingers Extending eXoskeleton (FEX) is a serial, under-actuated mechanism capable of executing fingers' extension. FEX is based on the state-of-art FingerSpine serial...
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Creating new voices using normalizing flows
PublicationCreating realistic and natural-sounding synthetic speech remains a big challenge for voice identities unseen during training. As there is growing interest in synthesizing voices of new speakers, here we investigate the ability of normalizing flows in text-to-speech (TTS) and voice conversion (VC) modes to extrapolate from speakers observed during training to create unseen speaker identities. Firstly, we create an approach for TTS...
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Paweł Rościszewski dr inż.
PeoplePaweł Rościszewski received his PhD in Computer Science at Gdańsk University of Technology in 2018 based on PhD thesis entitled: "Optimization of hybrid parallel application execution in heterogeneous high performance computing systems considering execution time and power consumption". Currently, he is an Assistant Professor at the Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Poland....
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Webquest- dobra praktyka w e-Learningu
PublicationW dobie informatyzacji i pokonywania barier wdrażania e-technologii na uczelniach wyższych uważa się, że jedną z najczęściej stosowanych aktywizujących technik nauczania wśród nauczycieli akademickich jest metoda projektu (ang. project-based learning). W niniejszym opracowaniu proponuje się zastosowanie w procesie edukacji na wyższej uczelni, metody webquest. Jest ona dużo rzadziej stosowana w praktyce. Opracowano ją w oparciu...
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Immersive Technologies that Aid Additive Manufacturing Processes in CBRN Defence Industry
PublicationTesting unique devices or their counterparts for CBRN (C-chemical, B-biological, R-radiological, N-nuclear) defense relies on additive manufacturing processes. Immersive technologies aid additive manufacturing. Their use not only helps understand the manufacturing processes, but also improves the design and quality of the products. This article aims to propose an approach to testing CBRN reconnaissance hand-held products developed...
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Leszek Ziemczonek dr
PeopleUniversity education 1973-1978 – Nicolaus Copernicus University in Toruń, University of Gdańsk in Gdańsk, Mathematical Physics, M. Sc. 1979 – Diploma of Postgraduate Studies, Pedagogics 1989 – Institute of Physics, Polish Academy of Sciences in Warsaw, Theoretical Physics, Ph. D. 2010-2012 – Diploma of Postgraduate Studies, Mathematics Training: · 09.1983 – Trieste (Italy) – International Centre for Theoretical Physics...
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Towards bees detection on images: study of different color models for neural networks
PublicationThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublicationDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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PROJEKTOWANIE STANOWISK LABORATORYJNYCH WSPIERAJĄCYCH PROCES SZKOLENIA PRAKTYCZNEGO KADR MORSKICH DZIAŁU MASZYNOWEGO W ŻEGLUDZE MIĘDZYNARODOWEJ, PRZYBRZEŻNEJ I KRAJOWEJ
PublicationWithin the article a design offer of the Department of Ship and Power Plants of the Faculty of Ocean Engineering And Ship Technology at the Gdansk University of Technology has been presented. The offer concerns designing laboratory stations which might stand for the equipment of a didactic base of maritime educational centers i.e. maritime (naval) academies and schools as well as maritime affairs' professional training centers,...
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Computer-assisted assessment of learning outcomes in the laboratory of metrology
PublicationIn the paper, didactic experience with broad and rapid continuous assessment of students’ knowledge, skills and competencies in the Laboratory of Metrology, which is an example of utilisation of assessment for learning, is presented. A learning management system was designed for manage, tracking, reporting of learning program and assessing learning outcomes. It has ability to provide with immediate feedback, which is used by the...
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Zastosowanie metody studium przypadku w kształceniu menedżerów
PublicationKształcenie z wykorzystaniem metod rozwiązywania problemów (problem-based learning) staje się coraz bardziej popularne na wszystkich poziomach kształcenia, również w edukacji biznesowej. Przykładem takiej metody jest studium przypadku (case study). Metoda studium przypadku pozwala na rozwijanie umiejętności i kompetencji wykorzystywanych przez menedżerów w ich pracy, np. umiejętności syntezy, identyfikacji problemów, czy podejmowania...
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Strategie treningu neuronowego estymatora częstotliwości tonu krtaniowego z użyciem generatora syntetycznych samogłosek
PublicationW wielu zastosowaniach telekomunikacyjnych pojawia się problem przetwarzania lub analizy sygnału mowy, w ramach którego, często w obszarze podstawowych algorytmów, stosuje się estymator częstotliwości tonu krtaniowego. Estymator rozpatrywany w tej pracy bazuje na neuronowym klasyfikatorze podejmującym decyzje na podstawie częstotliwości oraz mocy chwilowej wyznaczanych w podpasmach analizowanego sygnału mowy. W pracy rozważamy...
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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublicationA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublicationIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Program Erasmus Mundus : szansa na oryginalną formę kształcenia analityków
PublicationNową formą dydaktyki prowadzonej w roku akademickim 2009/2010 na Wydziale Chemicznym Politechniki Gdańskiej w ramach programu Erasmus Mundus są studia magisterskie European Master in Quality in Analytical Laboratories - EMQAL. Program ten wychodzi naprzeciw potrzebom europejskiego szkolnictwa wyższego związanym nie tylko ze stałym podnoszeniem jakości, atrakcyjności i innowacyjności kształcenia, ale również naprzeciw potrzebom...
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Justyna Signerska-Rynkowska dr inż.
PeopleI am currently an assistant professor (adjunct) at Gdansk University of Technology (Department of Differential Equations and Mathematics Applications). My scientific interests include dynamical systems theory, chaos theory and their applications to modeling of biological phenomena, especially to neurosciences. In June 2013 I completed PhD in Mathematics at the Institute of Mathematics of Polish Academy of Sciences (IMPAN) (thesis...
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Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices
PublicationThere are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Cross-Lingual Knowledge Distillation via Flow-Based Voice Conversion for Robust Polyglot Text-to-Speech
PublicationIn this work, we introduce a framework for cross-lingual speech synthesis, which involves an upstream Voice Conversion (VC) model and a downstream Text-To-Speech (TTS) model. The proposed framework consists of 4 stages. In the first two stages, we use a VC model to convert utterances in the target locale to the voice of the target speaker. In the third stage, the converted data is combined with the linguistic features and durations...
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Federated Learning in Healthcare Industry: Mammography Case Study
PublicationThe paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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Magdalena Barańska dr
PeopleAcademic teacher, vocational advisor, educator. Scientific interests: evolution of the role of the university, vocational and personnel guidance, designing an educational and professional career(career planning), lifelong learning. problems of academic education. Since 2010, I have been working with various institutions providing training, consulting, and educational services. 2013 Ph.D. in social sciences in the field of pedagogy...
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Horizon Europe proposals - Administrative Part
Open Research DataThe dataset contains data collected during the HE National Contact Point training on Oct. 12, 2022, reg. the administrative part of Horizon Europe grant proposals. The data set includes presentations concerning administrative forms of 2022 proposals and their content, including participant data; information about abstract writing, keyword choice and...
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MODELE TRANSFERU BIZNESU DOSTOSOWANE DO POTRZEB FIRM RODZINNYCH Z SEKTORA MSP W REGIONIE MORZA BAŁTYCKIEGO – CELE I ZADANIA W PROJEKCIE INBETS BSR
PublicationOpisano kontekst i cele projektu Innovative Business Transfer Models for SMEs in the BSR (INBETS BSR) współfinansowanego z Europejskiego Funduszu Rozwoju Regionalnego w ramach Programu Regionu Morza Bałtyckiego w latach 2014-2020. W projekt zaangażowanych jest czternastu partnerów z regionu Morza Bałtyckiego: Danii, Estonii, Finlandii, Litwy, Łotwy, Niemiec, Polski, Rosji i Szwecji. Rolę lidera projektu pełni Baltic Sea Academy...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Multiobjective Aerodynamic Optimization by Variable-Fidelity Models and Response Surface Surrogates
PublicationA computationally efficient procedure for multiobjective design optimization with variable-fidelity models and response surface surrogates is presented. The proposed approach uses the multiobjective evolutionary algorithm that works with a fast surrogate model, obtained with kriging interpolation of the low-fidelity model data enhanced by space-mapping correction exploiting a few high-fidelity training points. The initial Pareto...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publication—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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Automated Classifier Development Process for Recognizing Book Pages from Video Frames
PublicationOne 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...
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Gdańsk University of Technology graduates’ forms of raising qualifications – years 2017-2018
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the years 2017-2018 on the forms of raising their qualifications. The survey was conducted in the period from 2019 to 2020, two years after the respondents obtained graduate status. The research sample included 2909 respondents. To summarize, the most common...
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Gdańsk University of Technology graduates’ forms of raising qualifications – years 2011-2016
Open Research DataThe dataset includes data from the survey on the Gdańsk University of Technology graduates' from the years 2011-2016 on the forms of raising their qualifications. The survey was conducted in the period from 2013 to 2018, two years after the respondents obtained graduate status. The research sample included 9525 respondents. To summarize, the most common...
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Video of LEGO Bricks on Conveyor Belt Dataset Series
PublicationThe 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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AITP - AI Thermal Pedestrians Dataset
Open Research DataAITP is a pedestrian detection dataset consisting of 9178 annotated thermal images. The training set contains 7801 images on which15448 pedestrians were labeled. The test set has 1377 images on which 2731 objects were marked. All images are in PNG file format (120x160) captured with FLIR Lepton Thermal Camera on the streets of Gdańsk, Poland. All pedestrians...
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Problemy w szkoleniu i egzaminowaniu rowerzystów w Polsce
PublicationArtykuł przedstawia diagnozę problemów, które wpływają na jakość poziomu szkolenia i egzaminowania rowerzystów w Polsce. W pierwszej części zaprezentowano statystyki dotyczące wypadków z udziałem rowerzystów w Polsce, mających miejsce na przestrzeni ostatnich lat. Kolejno opisano obowiązujący system szkolenia oraz egzaminowania rowerzystów, a także nauczycieli i instruktorów. Dodatkowo ukazano przykłady dobrej praktyki, które stosują...
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Diagnosing wind turbine condition employing a neural network to the analysis of vibroacoustic signals
PublicationIt is important from the economic point of view to detect damage early in the wind turbines before failures occur. For this purpose, a monitoring device was built that analyzes both acoustic signals acquired from the built-in non-contact acoustic intensity probe, as well as from the accelerometers, mounted on the internal devices in the nacelle. The signals collected in this way are used for long-term training of the autoencoder...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublicationThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Podejście środowiskowe w dydaktyce projektowania Sustainable approach in teaching of design
PublicationThe aim of the paper is to assess the inclusion of academic teaching design to the process of sustainable development and proposals for an integrated approach in training architects. The article presents an original interpretation of environmental design in the field of architecture and urban planning. The significance of the environmental perspective is presented in the context of growing spatial and social fragmentation. The...
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Usefulness of Keystroke Dynamics Features in User Authentication and Emotion Recognition
PublicationThe study presented in the article focuses on keystroke dynamics analysis applied to recognize emotional states and to authenticate users. An overview of some studies and applications in these areas is presented. Then, an experiment is described, i.e. the way of collecting data, extracting features, training classifiers and finding out the most appropriate feature subsets. The results show that it is difficult to indicate a universal...
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FEEDB: A multimodal database of facial expressions and emotions
PublicationIn this paper a first version of a multimodal FEEDB database of facial expressions and emotions is presented. The database contains labeled RGB-D recordings of people expressing a specific set of expressions that have been recorded using Microsoft Kinect sensor. Such a database can be used for classifier training and testing in face recognition as well as in recognition of facial expressions and human emotions. Also initial experiences...
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Developing competences for cooperation in international teams - tools and methods
PublicationThe article presents the training methods that can be used to develop intercultural competences which are extremely important while working in intercultural teams. The mentioned methods like: case-studies, collaborating, role-play simulations, team working, video presentations and others are presented on the basis of authors’ experiences while teaching the international groups of students at Faculty of Management and Economics...
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Emotion Recognition and Its Applications
PublicationThe paper proposes a set of research scenarios to be applied in four domains: software engineering, website customization, education and gaming. The goal of applying the scenarios is to assess the possibility of using emotion recognition methods in these areas. It also points out the problems of defining sets of emotions to be recognized in different applications, representing the defined emotional states, gathering the data and...
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Functional safety and managing competence
PublicationSą nowe wyzwania związane z badaniami, edukacją i szkoleniem w obszarach bezpieczeństwa i ochrony systemów i sieci krytycznych. W rozdziale podkreśla się, że kompetencje specjalistów powinny być kształtowane w zintegrowanych procesach edukacji i szkolenia. Dlatego uzasadnione jest, aby opracować w Europie standardy i programy kształcenia na bazie odpowiednich prac badawczych i najlepszych doświadczeń z praktyki przemysłowej w celu...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Language material for English audiovisual speech recognition system developmen . Materiał językowy do wykorzystania w systemie audiowizualnego rozpoznawania mowy angielskiej
PublicationThe bi-modal speech recognition system requires a 2-sample language input for training and for testing algorithms which precisely depicts natural English speech. For the purposes of the audio-visual recordings, a training data base of 264 sentences (1730 words without repetitions; 5685 sounds) has been created. The language sample reflects vowel and consonant frequencies in natural speech. The recording material reflects both the...
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Reliable Microwave Modeling By Means of Variable-Fidelity Response Features
PublicationIn this work, methodologies for low-cost and reliable microwave modeling are presented using variable-fidelity response features. The two key components of our approach are: (i) a realization of the modeling process at the level of suitably selected feature points of the responses (e.g., S-parameters vs. frequency) of the structure at hand, and (ii) the exploitation of variable-fidelity EM simulation data, also for the response...
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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublicationWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Neural Oscillation During Mental Imagery in Sport: An Olympic Sailor Case Study
PublicationThe purpose of the current study was to examine the cortical correlates of imagery depending on instructional modality (guided vs. self-produced) using various sports-related scripts. According to the expert-performance approach, we took an idiosyncratic perspective analyzing the mental imagery of an experienced two-time Olympic athlete to verify whether different instructional modalities of imagery (i.e., guided vs. self-produced)...