Search results for: training - Bridge of Knowledge

Search

Search results for: training

Search results for: training

  • Rengel Cane Sia Doctoral Candidate

    People

    I’m Rengel, born and raised in the Philippines. As an undergraduate I did kinetic modeling on Copper-catalyzed atom transfer radical addition (ATRA). Then I was inspired to do both theoretical and experimental studies, which led me to propose my master’s thesis on Synthesis, Computational, Electrochemical, and Photoconductivity Studies on Naphthalene and its derivatives. This led to a master’s degree in Chemistry in the Mindanao...

  • Biometric identity verification

    Publication

    - Year 2022

    This chapter discusses methods which are capable of protecting automatic speaker verification systems (ASV) from playback attacks. Additionally, it presents a new approach, which uses computer vision techniques, such as the texture feature extraction based on Local Ternary Patterns (LTP), to identify spoofed recordings. We show that in this case training the system with large amounts of spectrogram patches may be difficult, and...

  • Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs

    Publication

    In 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...

    Full text available to download

  • Texture Features for the Detection of Playback Attacks: Towards a Robust Solution

    This paper describes the new version of a method that is capable of protecting automatic speaker verification (ASV) systems from playback attacks. The presented approach uses computer vision techniques, such as the texture feature extraction based on Local Ternary Patterns (LTP), to identify spoofed recordings. Our goal is to make the algorithm independent from the contents of the training set as much as possible; we look for the...

    Full text to download in external service

  • Active Learning Based on Crowdsourced Data

    The 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...

    Full text available to download

  • Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines

    Publication

    The 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...

  • Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features

    Publication

    - Year 2016

    This 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...

    Full text to download in external service

  • Massive Open Online Courses (MOOCs) in hospitality and tourism

    Publication
    • J. Murphy
    • N. Kalbaska
    • L. Cantoni
    • L. Horton-Tognazzini
    • P. Ryan
    • A. Williams

    - Year 2018

    The tourism industry, interesting and challenging, faces structural human resource problems such as skills shortages and staff turnover, seasonality and a high percentage of small to medium enterprises whose employees have limited time for training or education. Large tourism enterprises often span countries and continents, such as hotel chains, airlines, cruise companies and car rentals, where the employees need similar training...

    Full text to download in external service

  • Performance improvement of NN based RTLS by customization of NN structure - heuristic approach

    Publication

    - Year 2015

    The purpose of this research is to improve performance of the Hybrid Scene Analysis – Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis...

    Full text to download in external service

  • Computer-Supported Polysensory Integration Technology for Educationally Handicapped Pupils

    Publication

    In this paper, a multimedia system providing technology for hearing and visual attention stimulation is shortly presented. The system aims to support the development of educationally handicapped pupils. The system has been presented in the context of its configuration, architecture, and therapeutic exercise implementation issues. Results of pupils’ improvements after 8 weeks of training with the system are also provided. Training...

    Full text to download in external service

  • Adaptive CAD-Model Construction Schemes

    Two advanced surrogate model construction techniques are discussed in this paper. The models employ radial basis function (RBF)interpolation scheme or artificial neural networks (ANN) with a new training algorithm. Adaptive sampling technique is applied withrespect to all variables. Histograms showing the quality of the models are presented. While the quality of RBF models is satisfactory, theperformance of the ANN models obtained...

    Full text to download in external service

  • Natalia Sokół dr inż.

    BACKGROUND       Master of Science in Light and Lighting (2008-2009/11) The UCL Bartlett School of Graduate Studies, Faculty of the Built Environment, London, UK, www.bartlett.ucl.ac.uk       MA Degree in Interior Architecture (1999-2004), The Academy of Fine Arts, Poznan, Poland, www.uap.edu.pl       MA Degree in Art Education (1997-2002), Academy of Fine Arts, Poznan, Poland, www.uap.edu.pl MAIN RESEARCH AREAS ·         ...

  • Paweł Śliwiński dr hab. inż.

    Diplomas and academic degrees. Training 2017:   degree of habilitated doctor;2006:   PhD in Technical Sciences. PhD thesis defended with distinction. Gdansk University of Technology, Faculty of Mechanical Engineering.2000:   Master of Science. Graduated from the university with distinction. Gdansk University of Technology, Faculty of Mechanical Engineering.1995:   Mechanical technician. Graduated from a Technical Secondary School...

  • Kamila Kokot-Kanikuła mgr

    Kamila Kokot-Kanikuła is a digital media senior librarian at Gdańsk University of Technology (GUT) Library. She works in Digital Archive and Multimedia Creation Department and her main areas of interests include early printed books, digital libraries, Open Access and Open Science. In the Pomeranian Digital Library (PDL) Project she is responsible for creating annual digital plans, transferring files on digital platform, and promoting...

  • A review of emotion recognition methods based on keystroke dynamics and mouse movements

    Publication

    - Year 2013

    The paper describes the approach based on using standard input devices, such as keyboard and mouse, as sources of data for the recognition of users’ emotional states. A number of systems applying this idea have been presented focusing on three categories of research problems, i.e. collecting and labeling training data, extracting features and training classifiers of emotions. Moreover the advantages and examples of combining standard...

    Full text to download in external service

  • Dominika Wróblewska dr inż. arch.

    Dr. Eng. arch. Dominika Wróblewska, university professor, obtained the title of doctor of technical sciences in 2000. In 2002, she started working at the Faculty of Hydro and Environmental Engineering at the Gdańsk University of Technology (currently the Faculty of Civil and Environmental Engineering) as an assistant professor. Since 2019, he has been working as a university professor. The areas of interest are changes, introducing...

  • Recognizing emotions on the basis of keystroke dynamics

    Publication

    - Year 2015

    The article describes a research on recognizing emotional states on the basis of keystroke dynamics. An overview of various studies and applications of emotion recognition based on data coming from keyboard is presented. Then, the idea of an experiment is presented, i.e. the way of collecting and labeling training data, extracting features and finally training classifiers. Different classification approaches are proposed to be...

    Full text to download in external service

  • Color-based Detection of Bleeding in Endoscopic Images

    In this paper a color descriptor designed for bleeding detection in endoscopic images is proposed. The development of the algorithm was carried out on a representative training set of 36 images of bleeding and 25 clear images. Another 38 bleeding and 26 normal images were used in the final stage as a test set. All of the considered images were extracted from separate endoscopic examinations. The experiments include color distribution...

    Full text available to download

  • Musical Instrument Identification Using Deep Learning Approach

    Publication

    - SENSORS - Year 2022

    The 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...

    Full text available to download

  • Beata Krawczyk-Bryłka dr

    Psycholog, doktor nauk humanistycznych w dziedzinie zarządzania, adiunkt w Katedrze przedsiębiorczości. 2018 - 2021: Kierownik projektu NCN: „Efektuacyjny model zespołu przedsiębiorczego. Jak działają przedsiębiorcze zespoły odnoszące sukces" od 2016: Quality Standards Lead filaru People management & personal development na studiach MBA Politechniki Gdańskiej 2008 – 2012: Prodziekan ds kształcenia Wzydziału Zarządzania i Ekonomii...

  • Paweł Ziemiański dr

    Paweł Ziemiański - assistant professor at the Faculty of Management and Economics of the Gdańsk University of Technology. His research interests concern entrepreneurship, entrepreneurial intentions, and the dark side of entrepreneurship. He also conducted research regarding psychological aspects of exercising power in organizations. In teaching, he is interested in developing and using case studies. He took part in the training...

  • Towards Scalable Simulation of Federated Learning

    Federated 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...

    Full text to download in external service

  • Bees Detection on Images: Study of Different Color Models for Neural Networks

    Publication

    This paper presents an approach to bee detection in video streams using a neural network classifier. We describe the motivation for our research and the methodology of data acquisition. The main contribution to this work is a comparison of different color models used as an input format for a feedforward convolutional architecture applied to bee detection. The detection process has is based on a neural binary classifier that classifies...

    Full text available to download

  • Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia

    Publication

    - Year 2024

    W 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...

    Full text available to download

  • Train the trainer course

    Publication

    - Year 2018

    This chapter presents the concept, evaluation and evaluation results for the train the trainer. This concept of train the trainers is prepared within Workpackage 5 of EU-funded project: MASTER BSR (Erasmus+ Strategic Partnership Programme). Due to the nature of adult learning the content is designed for the use of participatory methods (involved, active). This method uses various techniques of active learning e.g. group work,...

    Full text to download in external service

  • Development and test of fex, a fingers extending exoskeleton for rehabilitation and regaining mobility

    Publication

    - International Journal of Mechanics and Control - Year 2018

    This 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...

    Full text to download in external service

  • Creating new voices using normalizing flows

    Publication
    • P. Biliński
    • T. Merritt
    • A. Ezzerg
    • K. Pokora
    • S. Cygert
    • K. Yanagisawa
    • R. Barra-Chicote
    • D. Korzekwa

    - Year 2022

    Creating 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...

    Full text available to download

  • Narzędzia treningu twórczości jako pomoc w kształceniu projektantów

    Publication

    - Year 2016

    Kreatywność rozwijać. Na tym założeniu opiera się międzynarodowy program edukacyjny Odyssey of the Mind (Odyseja Umysłu). W programie zespoły młodych osób pracują metodą projektową, wykorzystując różnorodne techniki treningu twórczości, nad rozwiązaniem abstrakcyjnego problemu rozbieżnego. Część absolwentów programu wybiera kierunki kreatywne jako naturalną kontynuację procesu edukacji. Elementy treningu twórczości można wykorzystać...

  • Paweł Rościszewski dr inż.

    People

    Paweł 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....

  • Immersive Technologies that Aid Additive Manufacturing Processes in CBRN Defence Industry

    Publication
    • M. Gawlik-Kobylińska
    • P. Maciejewski
    • J. Lebiedź
    • A. Kravcov

    - International Journal on Information Technologies and Security - Year 2021

    Testing 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...

    Full text to download in external service

  • Towards bees detection on images: study of different color models for neural networks

    Publication

    This 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...

  • Automated detection of pronunciation errors in non-native English speech employing deep learning

    Publication

    - Year 2023

    Despite 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...

    Full text available to download

  • PROJEKTOWANIE STANOWISK LABORATORYJNYCH WSPIERAJĄCYCH PROCES SZKOLENIA PRAKTYCZNEGO KADR MORSKICH DZIAŁU MASZYNOWEGO W ŻEGLUDZE MIĘDZYNARODOWEJ, PRZYBRZEŻNEJ I KRAJOWEJ

    Within 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,...

    Full text available to download

  • Computer-assisted assessment of learning outcomes in the laboratory of metrology

    Publication

    - Year 2015

    In 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...

  • Zastosowanie metody studium przypadku w kształceniu menedżerów

    Publication

    Kształcenie 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...

    Full text available to download

  • Strategie treningu neuronowego estymatora częstotliwości tonu krtaniowego z użyciem generatora syntetycznych samogłosek

    W 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...

    Full text available to download

  • Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks

    Publication

    A 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...

    Full text to download in external service

  • Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention

    Publication

    - Year 2021

    This 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...

    Full text available to download

  • INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY

    In 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...

  • Justyna Signerska-Rynkowska dr inż.

    I 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...

  • Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices

    Publication
    • A. G. Pereira
    • A. Ojo
    • C. Edward
    • L. Porwol

    - Year 2020

    There 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...

    Full text available to download

  • Cross-Lingual Knowledge Distillation via Flow-Based Voice Conversion for Robust Polyglot Text-to-Speech

    Publication
    • D. Piotrowski
    • R. Korzeniowski
    • A. Falai
    • S. Cygert
    • K. Pokora
    • G. Tinchev
    • Z. Zhang
    • K. Yanagisawa

    - Year 2023

    In 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...

    Full text to download in external service

  • Federated Learning in Healthcare Industry: Mammography Case Study

    The 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...

    Full text to download in external service

  • Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning

    Publication
    • F. Szatkowski
    • M. Pyła
    • M. Przewięźlikowski
    • S. Cygert
    • B. Twardowski
    • T. Trzciński

    - Year 2024

    In 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...

    Full text to download in external service

  • Horizon Europe proposals - Administrative Part

    The 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...

  • MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences

    Publication
    • S. R. Gupte
    • D. S. Jain
    • A. Srinivasan
    • R. Aduri

    - Year 2020

    —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...

    Full text to download in external service

  • Automated Classifier Development Process for Recognizing Book Pages from Video Frames

    One 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...

    Full text to download in external service

  • Playback detection using machine learning with spectrogram features approach

    Publication

    - Year 2017

    This 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...

    Full text available to download

  • Multiobjective Aerodynamic Optimization by Variable-Fidelity Models and Response Surface Surrogates

    Publication

    - AIAA JOURNAL - Year 2016

    A 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...

    Full text to download in external service

  • Gdańsk University of Technology graduates’ forms of raising qualifications – years 2017-2018

    Open Research Data
    open access

    The 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...