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Wyniki wyszukiwania dla: training

Wyniki wyszukiwania dla: training

  • Urszula Szybowska mgr

    Zawodowo zajmuje się rozwijaniem działań w zakresie obsługi i kształcenia polskich i zagranicznych użytkowników Biblioteki PG oraz w zakresie rozwoju i promowania projektów mobilnościowych w ramach programu Erasmus+. W latach 2017-2020 koordynator ds. współpracy międzynarodowej w Bibliotece PG ; od roku 2020 koordynator ds. programu Erasmus+ w Bibliotece PG ; 2018-2023 bibliotekarz ds. mediów społecznościowych Biblioteki Politechniki...

  • Łukasz Bugalski dr inż. arch.

    Łukasz Bugalski ukończył studia na kierunku Architektura i Urbanistyka (2013) oraz obronił doktorat (2013-2018) z tej samej dyscypliny naukowej (Politechnika Gdańska). Był stypendystą programu Marie Skłodowska-Curie (2017-2020) w zakresie critical heritage studies jako część projektu "CHEurope" (MSCA Innovative Training Network) odbytego w Istituto per i Beni Artistici, Culturali e Naturali della Regione Emilia-Romagna w Bolonii...

  • Rengel Cane Sia Doctoral Candidate

    Osoby

    I'm Rengel, born and raised in the Philippines.  I joined the Gdansk University of Technology in October 2019 as a Maria Skłodowska-Curie early-stage researcher. Calculating the Photophysics of molecular logic sensors for the early detection of atherosclerosis - a precursor to the world's leading causes of death.  I'm a professional bass player. I play music to relieve stress and express creativity. I also like reading fantasy...

  • Piotr Lorens prof. dr hab. inż. arch.

    Piotr Lorens – prof. dr hab. inż. arch., prof. nzw. Politechniki Gdańskiej. Po ukończeniu studiów w 1994 roku podjął pracę w Zakładzie Rozwoju Miasta na Wydziale Architektury Politechniki Gdańskiej. Uzyskawszy Stypendium Fulbrighta wyjechał na staż do USA, gdzie w latach 1996-1997 ukończył Special Program for Urban and Regional Studies na Massachusetts Institute of Technology oraz International Training Program na Harvard University...

  • Magdalena Szuflita-Żurawska

    Magdalena Szuflita-Żurawska jest kierownikiem Sekcji Informacji Naukowo-Technicznej na Politechnice Gdańskiej oraz Liderem Centrum Kompetencji Otwartej Nauki przy Bibliotece Politechniki Gdańskiej. Jej główne zainteresowania badawcze koncentrują się w obszarze komunikacji naukowej oraz otwartych danych badawczych, a także motywacji i produktywności naukowej. Jest odpowiedzialna między innymi za prowadzenie szkoleń dla pracowników...

  • Leszek Pawłowski dr

    Dr Leszek Pawłowski, PhD, lawyer, assistant professor at the Department of Palliative Medicine, Medical University of Gdańsk (Poland), member of Polish Working Group on End-of-Life Ethics and Editorial Board member of the journal Palliative Medicine in Practice. His research is focused on legal issues in palliative care, hospice and palliative care volunteering, Advance Care Planning and medical law. He is involved in healthcare...

  • Multiscaled Hybrid Features Generation for AdaBoost Object Detection

    This work presents the multiscaled version of modified census features in graphical objects detection with AdaBoost cascade training algorithm. Several experiments with face detector training process demonstrate better performance of such features over ordinal census and Haar-like approaches. The possibilities to join multiscaled census and Haar features in single hybrid cascade of strong classifiers are also elaborated and tested....

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  • Biometric identity verification

    Publikacja

    - Rok 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...

  • Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer

    Publikacja
    • N. Van
    • P. Paramasivam
    • M. Dzida
    • S. M. Osman
    • D. T. N. Le
    • D. N. Cao
    • T. H. Truong
    • V. D. Tran

    - Case Studies in Thermal Engineering - Rok 2024

    In this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...

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

    Publikacja

    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...

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  • 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...

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  • 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...

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  • Paweł Śliwiński dr hab. inż.

    Stopnie naukowe marzec 2017 – nadanie stopnia doktora habilitowanego;2006 – doktor nauk technicznych (praca doktorska obroniona na Wydziale Mechanicznym PG z wyróżnieniem);2001–2006 – studia doktoranckie „Nowoczesne Technologie i Konwersja Energii” przy Wydziale Mechanicznym Politechniki Gdańskiej; Informacje o dotychczasowym zatrudnieniu: od 01.07.2018 - profesor uczelni, Wydział Mechanicznyod 01.05.2017 – adiunkt, Wydział Mechaniczny...

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

    Publikacja

    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

    Publikacja

    - Rok 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...

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

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

    - Rok 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...

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

    Publikacja

    - Rok 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...

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  • Computer-Supported Polysensory Integration Technology for Educationally Handicapped Pupils

    Publikacja

    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...

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  • Dominika Wróblewska dr inż. arch.

    Dr inż. arch. Dominika Wróblewska, profesor uczelni uzyskała tytuł doktora nauk technicznych w 2000 roku. Od 2002 roku rozpoczęła pracę na wydziale Budownictwa Wodnego i Inżynierii Środowiska na Politechnice Gdańskiej (obecnie wydział Inżynierii Lądowej i Środowiska) na stanowisku adiunkta. Od  2019 roku  pracuje na stanowisku profesora uczelni. Obszary zainteresowań to zmiany wprowadzanie edukacji opartej na interdyscyplinarnym...

  • 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...

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  • 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 ·         ...

  • 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 - adiunkt na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej. Jego zainteresowania badawcze dotyczą przedsiębiorczości, zespołów przedsiębiorczych oraz negatywnych aspektów (ciemnej strony) przedsiębiorczości. Prowadził również badania dotyczące psychologicznych aspektów sprawowania władzy w organizacjach. W działalności dydaktycznej interesuje go praca ze studium przypadku. Brał udział w szkoleniu z nauczania...

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

    Publikacja

    - Rok 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...

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  • Recognizing emotions on the basis of keystroke dynamics

    Publikacja

    - Rok 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...

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  • 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...

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  • Musical Instrument Identification Using Deep Learning Approach

    Publikacja

    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...

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  • 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...

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

    Publikacja

    - Rok 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...

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

    Publikacja

    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...

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  • Kamila Kokot-Kanikuła mgr

    Kamila Kokot-Kanikuła pracuje w Bibliotece Politechniki Gdańskiej w Sekcji Budowy Zbiorów Cyfrowych i Multimedialnych na stanowisku starszego bibliotekarza. Jest absolwentką Instytutu Historycznego oraz Informacji Naukowej i Bibliotekoznawstwa na Uniwersytecie Wrocławskim. Główne kierunki zainteresowań to starodruki, biblioteki cyfrowe, repozytoria instytucjonalne, Otwarte Zasoby Edukacyjne, Open Access i Open Data. W bibliotece...

  • Paweł Rościszewski dr inż.

    Osoby

    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....

  • Train the trainer course

    Publikacja

    - Rok 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,...

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

    Publikacja

    - International Journal of Mechanics and Control - Rok 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...

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  • Creating new voices using normalizing flows

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

    - Rok 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...

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  • Narzędzia treningu twórczości jako pomoc w kształceniu projektantów

    Publikacja

    - Rok 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...

  • Arsalan Muhammad Soomar Doctoral Student

    Osoby

    Hi, I'm Arsalan Muhammad Soomar, an Electrical Engineer. I received my Master's and Bachelor's Degree in the field of Electrical Engineering from Mehran University of Engineering and Technology, Jamshoro, Sindh, Pakistan.  Currently enrolled as a Doctoral student at the Gdansk University of Technology, Gdansk, Poland. Also worked in Yellowlite. INC, Ohio  as a Solar Design Engineer.   HEADLINE Currently Enrolled as a Doctoral...

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

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

    - International Journal on Information Technologies and Security - Rok 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...

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  • Mykola Lukianov mgr

    Mykola Lukianov received a B.Sc. and M.Sc degree in Electronics and Communications from the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” in 2018 and 2020 respectively. He is currently a PhD student at the Gdansk University of Technology, Poland and a researcher group member in project SMARTGYsum “Research and Training Network for Smart and Green Energy Systems and Business Models”. His research...

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

    Publikacja

    - Rok 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...

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

    Publikacja

    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...

  • Zastosowanie metody studium przypadku w kształceniu menedżerów

    Publikacja

    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...

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  • Justyna Signerska-Rynkowska dr inż.

    Since 2021 visiting assistant professor in Dioscuri Centre in Topological Data Analysis (Institute of Mathematics of the Polish Academy of Sciences, IMPAN)  Since 2016   assistant professor at Gdańsk University of Technology, Faculty of Applied Physics and                      Mathematics, Department of Differential Equations and Mathematics Applications  2020 - 2023  Principal Investigator in "SONATA" grant “Challenges of low-dimensional...

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

    Publikacja

    - Rok 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...

  • 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,...

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  • 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...

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

    Publikacja

    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...

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  • 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...

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

    Publikacja

    - Rok 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...

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

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

    - Rok 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...

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