Search results for: SYSTEM TESTING , SENSITIVITY , COMPUTATIONAL MODELING , NEURAL NETWORKS , OBJECT DETECTION , DISTORTION , DATA MODELS - Bridge of Knowledge

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Search results for: SYSTEM TESTING , SENSITIVITY , COMPUTATIONAL MODELING , NEURAL NETWORKS , OBJECT DETECTION , DISTORTION , DATA MODELS
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Search results for: SYSTEM TESTING , SENSITIVITY , COMPUTATIONAL MODELING , NEURAL NETWORKS , OBJECT DETECTION , DISTORTION , DATA MODELS

  • Robustness in Compressed Neural Networks for Object Detection

    Publication

    - Year 2021

    Model compression techniques allow to significantly reduce the computational cost associated with data processing by deep neural networks with only a minor decrease in average accuracy. Simultaneously, reducing the model size may have a large effect on noisy cases or objects belonging to less frequent classes. It is a crucial problem from the perspective of the models' safety, especially for object detection in the autonomous driving...

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  • Wiktoria Wojnicz dr hab. inż.

    DSc in Mechanics (in the field of Biomechanics)  - Lodz Univeristy of Technology, 2019 PhD in Mechanics (in the field of Biomechanics)  - Lodz Univeristy of Technology, 2009 (with distinction)   List of papers (2009 - ) Wojnicz W., Wittbrodt E., Analysis of muscles' behaviour. Part I. The computational model of muscle. Acta of Bioengineering and Biomechanics, Vol. 11, No.4, 2009, p. 15-21 Wojnicz W., Wittbrodt E., Analysis of...

  • Adaptacyjny system oświetlania dróg oraz inteligentnych miast

    Publication

    - Year 2024

    Przedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...

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  • Piotr Szczuko dr hab. inż.

    Piotr Szczuko received his M.Sc. degree in 2002. His thesis was dedicated to examination of correlation phenomena between perception of sound and vision for surround sound and digital image. He finished Ph.D. studies in 2007 and one year later completed a dissertation "Application of Fuzzy Rules in Computer Character Animation" that received award of Prime Minister of Poland. His interests include: processing of audio and video, computer...

  • 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...

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  • Deep neural networks for data analysis 24/25

    e-Learning Courses
    • J. Cychnerski
    • K. Draszawka

    This course covers introduction to supervised machine learning, construction of basic artificial deep neural networks (DNNs) and basic training algorithms, as well as the overview of popular DNNs architectures (convolutional networks, recurrent networks, transformers). The course introduces students to popular regularization techniques for deep models. Besides theory, large part of the course is the project in which students apply...

  • 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...

  • Magdalena Szuflita-Żurawska

    Head of the Scientific and Technical Information Services at the Gdansk University of Technology Library and the Leader of the Open Science Competence Center. She is also a Plenipotentiary of the Rector of the Gdańsk University of Technology for open science.  She is a PhD Candidate. Her main areas of research and interests include research productivity, motivation, management of HEs, Open Access, Open Research Data, information...

  • A survey of neural networks usage for intrusion detection systems

    In recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...

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  • Deep neural networks for data analysis

    e-Learning Courses
    • K. Draszawka

    The aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...