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Wyniki wyszukiwania dla: Machine Learning
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Artificial intelligence for software development — the present and the challenges for the future
PublikacjaSince the time when first CASE (Computer-Aided Software Engineering) methods and tools were developed, little has been done in the area of automated creation of code. CASE tools support a software engineer in creation the system structure, in defining interfaces and relationships between software modules and, after the code has been written, in performing testing tasks on different levels of detail. Writing code is still the task...
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Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis
PublikacjaNumerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending...
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A Bayesian regularization-backpropagation neural network model for peeling computations
PublikacjaA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
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Classifying Emotions in Film Music - A Deep Learning Approach
PublikacjaThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial 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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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublikacjaIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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A note on the affective computing systems and machines: a classification and appraisal
PublikacjaAffective computing (AfC) is a continuously growing multidisciplinary field, spanning areas from artificial intelligence, throughout engineering, psychology, education, cognitive science, to sociology. Therefore, many studies have been devoted to the aim of addressing numerous issues, regarding different facets of AfC solutions. However, there is a lack of classification of the AfC systems. This study aims to fill this gap by reviewing...
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Multiscaled Hybrid Features Generation for AdaBoost Object Detection
PublikacjaThis 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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Labeler-hot Detection of EEG Epileptic Transients
PublikacjaPreventing early progression of epilepsy and sothe severity of seizures requires effective diagnosis. Epileptictransients indicate the ability to develop seizures but humansoverlook such brief events in an electroencephalogram (EEG)what compromises patient treatment. Traditionally, trainingof the EEG event detection algorithms has relied on groundtruth labels, obtained from the consensus...
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Kamil Stasiak mgr inż.
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Michał Czubenko dr inż.
OsobyMichał Czubenko jest wyróżniającym się absolwentem z 2009 roku Wydziału Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej, specjalizującym się w dyscyplinie automatyka i robotyka. Obecnie pełni funkcję adiunkta w Katedrze Systemów Decyzyjnych i Robotyki tej samej uczelni. W 2012 roku odbył trzymiesięczny staż na Kingston University London, poszerzając swoje horyzonty w tej dziedzinie. Od obrony pracy magisterskiej...
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Hubert Anysz dr inż.
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Daniel Węsierski dr inż.
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Tymoteusz Cejrowski dr inż.
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Oskar Wysocki
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Maciej Majewski dr hab. inż.
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Hammed Adeleye Adeleye Mojeed
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Tomasz Nowakowski dr inż.
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Agnieszka Mikołajczyk-Bareła dr inż.
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Aleksandra Nabożny dr inż.
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Dawid Wieczerzak mgr inż.
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Vorya Waladi
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Jarosław Jóźwik
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Wiktoria Kozak
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Maria Ferlin MSc
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Khansa Gulshad
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Łukasz Witanowski dr inż.
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Kacper Cierpiak
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Faramarz Bagherzadeh MSc.
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Tomasz Menet mgr inż.
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Natalia Ziółkowska mgr inż.
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Paulina Alicja Leszczełowska
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Bartosz Grajewski
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Szymon Zdybel
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Nastaran Hamedi
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Rafał Wolniak
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Adam Wawrzyński
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Łukasz Witanowski
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Dharm Jain
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Faizullah Jan MSc
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