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    Wyświetlanie 1-3 z 3
    Tytuł:
    Image Retrieval Based on Text and Visual Content Using Neural Networks
    Autorzy:
    Castro, D. A.
    Seijas, L. M.
    Powiązania:
    https://bibliotekanauki.pl/articles/108732.pdf
    Data publikacji:
    2010
    Wydawca:
    Społeczna Akademia Nauk w Łodzi
    Tematy:
    image retrieval
    Self-Organizing Maps (SOM)
    content-based image retrieval (CBIR)
    Text-Based Image Retrieval (TBIR)
    ParBSOM
    Scoring function
    Opis:
    In the last few years there has been a dramatic increase in the amount of visual data to be searched and retrieved. Typically, images are described by their textual content (TBIR) or by their visual features (CBIR). However, these approaches still present many problems. The hybrid approach was recently introduced, combining both characteristics to improve the benefits of using text and visual content separately. In this work we examine the use of the Self Organizing Maps for content-based image indexing and retrieval. We propose a scoring function which eliminates irrelevant images from the results and we also introduce a SOM variant (ParBSOM) that reduces training and retrieval times. The application of these techniques to the hybrid approach improved computational results.
    Źródło:
    Journal of Applied Computer Science Methods; 2010, 2 No. 1; 21-39
    1689-9636
    Pojawia się w:
    Journal of Applied Computer Science Methods
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multiscale evaluation of a thin-bed reservoir
    Autorzy:
    Lis-Śledziona, Anita
    Powiązania:
    https://bibliotekanauki.pl/articles/1841759.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    thin beds
    high resolution well logs prediction
    horizontal resistivity
    unsupervised neural network
    self-organizing maps (SOM)
    electrofacies
    low resistivity pay
    Opis:
    A thin-bed laminated shaly-sand reservoir of the Miocene formation was evaluated using two methods: high resolution microresistivity data from the XRMI tool and conventional well logs. Based on high resolution data, the Earth model of the reservoir was defined in a way that allowed the analyzed interval to be subdivided into thin layers of sandstones, mudstones, and claystones. Theoretical logs of gamma ray, bulk density, horizontal and vertical resistivity were calculated based on the forward modeling method to describe the petrophysical properties of individual beds and calculate the clay volume, porosity, and water saturation. The relationships amongst the contents of minerals were established based on the XRD data from the neighboring wells; hence, the high-resolution lithological model was evaluated. Predicted curves and estimated volumes of minerals were used as an input in multimineral solver and based on the assumed petrophysical model the input data were recalculated, reconstructed and compared with the predicted curves. The volumes of minerals and input curves were adjusted during several runs to minimalize the error between predicted and recalculated variables. Another approach was based on electrofacies modeling using unsupervised self-organizing maps. As an input, conventional well logs were used. Then, the evaluated facies model was used during forward modeling of the effective porosity, horizontal resistivity and water saturation. The obtained results were compared and, finally, the effective thickness of the reservoir was established based on the results from the two methods.
    Źródło:
    Geology, Geophysics and Environment; 2021, 47, 1; 5-20
    2299-8004
    2353-0790
    Pojawia się w:
    Geology, Geophysics and Environment
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Music Mood Visualization Using Self-Organizing Maps
    Autorzy:
    Plewa, M.
    Kostek, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/176410.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    music mood
    music parameterization
    MER (Music Emotion Recognition)
    MIR (Music Information Retrieval)
    Multidimensional Scaling (MDS)
    principal component analysis (PCA)
    Self-Organizing Maps (SOM)
    ANN (Artificial Neural Networks)
    Opis:
    Due to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which music excerpts with similar mood are organized next to each other on the two-dimensional display.
    Źródło:
    Archives of Acoustics; 2015, 40, 4; 513-525
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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