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    Wyświetlanie 1-5 z 5
    Tytuł:
    Semantic hashing for fast solar magnetogram retrieval
    Autorzy:
    Grycuk, Rafał
    Scherer, Rafał
    Marchlewska, Alina
    Napoli, Christian
    Powiązania:
    https://bibliotekanauki.pl/articles/2147145.pdf
    Data publikacji:
    2022
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    content-based image retrieval
    image descriptor
    solar analysis
    Opis:
    We propose a method for content-based retrieving solar magnetograms. We use the SDO Helioseismic and Magnetic Imager output collected with SunPy PyTorch libraries. We create a mathematical representation of the magnetic field regions of the Sun in the form of a vector. Thanks to this solution we can compare short vectors instead of comparing full-disk images. In order to decrease the retrieval time, we used a fully-connected autoencoder, which reduced the 256-element descriptor to a 32-element semantic hash. The performed experiments and comparisons proved the efficiency of the proposed approach. Our approach has the highest precision value in comparison with other state-of-the-art methods. The presented method can be used not only for solar image retrieval but also for classification tasks.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 4; 299--306
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fast image index for database management engines
    Autorzy:
    Grycuk, Rafał
    Najgebauer, Patryk
    Kordos, Miroslaw
    Scherer, Magdalena M.
    Marchlewska, Alina
    Powiązania:
    https://bibliotekanauki.pl/articles/1837480.pdf
    Data publikacji:
    2020
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    image descriptor
    content-based image retrieval
    image indexing
    Opis:
    Large-scale image repositories are challenging to perform queries based on the content of the images. The paper proposes a novel, nested-dictionary data structure for indexing image local features. The method transforms image local feature vectors into two-level hashes and builds an index of the content of the images in the database. The algorithm can be used in database management systems. We implemented it with an example image descriptor and deployed in a relational database. We performed the experiments on two image large benchmark datasets.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 2; 113-123
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Radon‐wavelet based novel image descriptor for mammogram mass classification
    Autorzy:
    Obaidullah, Sk Md
    Ahmed, Sajib
    Gonçalves, Teresa
    Rato, Luís
    Powiązania:
    https://bibliotekanauki.pl/articles/384195.pdf
    Data publikacji:
    2020
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    image descriptor
    radon transform
    mammography
    breast cancer
    classification
    Opis:
    Mammography based breast cancer screening is very popular because of its lower costing and readily availability. For automated classification of mammogram images as benign or malignant machine learning techniques are involved. In this paper, a novel image descriptor which is based on the idea of Radon and Wavelet transform is proposed. This method is quite efficient as it performs well without any clinical information. Performance of the method is evaluated using six different classifiers namely: Bayesian network (BN), Linear discriminant analysis (LDA), Logistic, Support vector machine (SVM), Multilayer perceptron (MLP) and Random Forest (RF) to choose the best performer. Considering the present experimental framework, we found, in terms of area under the ROC curve (AUC), the proposed image descriptor outperforms, upto some extent, previous reported experiments using histogram based hand‐crafted methods, namely Histogram of Oriented Gradient (HOG) and Histogram of Gradient Divergence (HGD) and also Convolution Neural Network (CNN). Our experimental results show the highest AUC value of 0.986, when using only the carniocaudal (CC) view compared to when using only the mediolateral oblique (MLO) (0.738) or combining both views (0.838). These results thus proves the effectiveness of CC view over MLO for better mammogram mass classification.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 2; 74-80
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Detecting visual objects by edge crawling
    Autorzy:
    Grycuk, Rafał
    Wojciechowski, Adam
    Wei, Wei
    Siwocha, Agnieszka
    Powiązania:
    https://bibliotekanauki.pl/articles/1837538.pdf
    Data publikacji:
    2020
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    content-based image retrieval
    crawler
    edge detection
    image descriptor
    object extraction
    Opis:
    Content-based image retrieval methods develop rapidly with a growing scale of image repositories. They are usually based on comparing and indexing some image features. We developed a new algorithm for finding objects in images by traversing their edges. Moreover, we describe the objects by histograms of local features and angles. We use such a description to retrieve similar images fast. We performed extensive experiments on three established image datasets proving the effectiveness of the proposed method.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 3; 223-237
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Development of a Reverse-search System of Similar or Identical Images
    Autorzy:
    Veres, O.
    Kis, Ya.
    Kugivchak, V.
    Rishniak, I.
    Powiązania:
    https://bibliotekanauki.pl/articles/410994.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Oddział w Lublinie PAN
    Tematy:
    analysis
    detector
    descriptor
    image
    key point
    method
    pixel
    hashing
    Opis:
    The article describes the research of image analysis methods. The methods of indexing images for the search of duplicate images, as well as methods for finding similar images based on the definition of key points are described. The prototype of the system was created, and testing of the described methods was carried out. The result of the analysis became the basis for the information system project of reverse search of similar or identical images.
    Źródło:
    ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes; 2018, 7, 2; 23-30
    2084-5715
    Pojawia się w:
    ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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