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    Wyświetlanie 1-8 z 8
    Tytuł:
    On training deep neural networks using a streaming approach
    Autorzy:
    Duda, Piotr
    Jaworski, Maciej
    Cader, Andrzej
    Wang, Lipo
    Powiązania:
    https://bibliotekanauki.pl/articles/91796.pdf
    Data publikacji:
    2020
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    deep learning
    data streams
    convolutional neural networks
    strumienie danych
    konwolucyjne sieci neuronowe
    Opis:
    In recent years, many deep learning methods, allowed for a significant improvement of systems based on artificial intelligence methods. Their effectiveness results from an ability to analyze large labeled datasets. The price for such high accuracy is the long training time, necessary to process such large amounts of data. On the other hand, along with the increase in the number of collected data, the field of data stream analysis was developed. It enables to process data immediately, with no need to store them. In this work, we decided to take advantage of the benefits of data streaming in order to accelerate the training of deep neural networks. The work includes an analysis of two approaches to network learning, presented on the background of traditional stochastic and batch-based methods.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 1; 15-26
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A new approach to image-based recommender systems with the application of heatmaps maps
    Autorzy:
    Woldan, Piotr
    Duda, Piotr
    Cader, Andrzej
    Laktionov, Ivan
    Powiązania:
    https://bibliotekanauki.pl/articles/2201330.pdf
    Data publikacji:
    2023
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    feature extraction
    recommender system
    heatmap
    Opis:
    One of the fundamental issues of modern society is access to interesting and useful content. As the amount of available content increases, this task becomes more and more challenging. Our needs are not always formulated in words; sometimes we have to use complex data types like images. In this paper, we consider the three approaches to creating recommender systems based on image data. The proposed systems are evaluated on a real-world dataset. Two case studies are presented. The first one presents the case of an item with many similar objects in a database, and the second one with only a few similar items
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 2; 63--72
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Noise robust illumination invariant face recognition via bivariate wavelet shrinkage in logarithm domain
    Autorzy:
    Chen, Guang Yi
    Krzyżak, Adam
    Duda, Piotr
    Cader, Andrzej
    Powiązania:
    https://bibliotekanauki.pl/articles/2147140.pdf
    Data publikacji:
    2022
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    face recognition
    dual-tree complex wavelet transforms
    DTCWT
    collaborative representation-based classifier
    CRC
    invariant features
    pattern recognition
    computer vision
    Opis:
    Recognizing faces under various lighting conditions is a challenging problem in artificial intelligence and applications. In this paper we describe a new face recognition algorithm which is invariant to illumination. We first convert image files to the logarithm domain and then we implement them using the dual-tree complex wavelet transform (DTCWT) which yields images approximately invariant to changes in illumination change. We classify the images by the collaborative representation-based classifier (CRC). We also perform the following sub-band transformations: (i) we set the approximation sub-band to zero if the noise standard deviation is greater than 5; (ii) we then threshold the two highest frequency wavelet sub-bands using bivariate wavelet shrinkage. (iii) otherwise, we set these two highest frequency wavelet sub-bands to zero. On obtained images we perform the inverse DTCWT which results in illumination invariant face images. The proposed method is strongly robust to Gaussian white noise. Experimental results show that our proposed algorithm outperforms several existing methods on the Extended Yale Face Database B and the CMU-PIE face database.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 3; 169--180
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evolutionary algorithm with a configurable search mechanism
    Autorzy:
    Łapa, Krystian
    Cpałka, Krzysztof
    Laskowski, Łukasz
    Cader, Andrzej
    Zeng, Zhigang
    Powiązania:
    https://bibliotekanauki.pl/articles/1837536.pdf
    Data publikacji:
    2020
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    evolutionary algorithm
    population-based algorithm
    optimization
    operator pool
    operator selection
    individual selection
    Opis:
    In this paper, we propose a new population-based evolutionary algorithm that automatically configures the used search mechanism during its operation, which consists in choosing for each individual of the population a single evolutionary operator from the pool. The pool of operators comes from various evolutionary algorithms. With this idea, a flexible balance between exploration and exploitation of the problem domain can be achieved. The approach proposed in this paper might offer an inspirational alternative in creating evolutionary algorithms and their modifications. Moreover, different strategies for mutating those parts of individuals that encode the used search operators are also taken into account. The effectiveness of the proposed algorithm has been tested using typical benchmarks used to test evolutionary algorithms.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 3; 151-171
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Monitoring regenerative heat exchanger in steam power plant by making use of the recurrent neural network
    Autorzy:
    Niksa-Rynkiewicz, Tacjana
    Szewczuk-Krypa, Natalia
    Witkowska, Anna
    Cpałka, Krzysztof
    Zalasiński, Marcin
    Cader, Andrzej
    Powiązania:
    https://bibliotekanauki.pl/articles/2031128.pdf
    Data publikacji:
    2021
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    recurrent neural network
    intelligent industrial monitoring
    Almeida–Pineda recurrent back-propagation
    regenerative heat exchanger
    steam power plant
    Opis:
    Artificial Intelligence algorithms are being increasingly used in industrial applications. Their important function is to support operation of diagnostic systems. This paper presents a new approach to the monitoring of a regenerative heat exchanger in a steam power plant, which is based on a specific use of the Recurrent Neural Network (RNN). The proposed approach was tested using real data. This approach can be easily adapted to similar monitoring applications of other industrial dynamic objects.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 2; 143-155
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-8 z 8

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