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pro vyhledávání: '"Aksoy, Selim."'
Multisource image analysis that leverages complementary spectral, spatial, and structural information benefits fine-grained object recognition that aims to classify an object into one of many similar subcategories. However, for multisource tasks that
Externí odkaz:
http://arxiv.org/abs/2105.10983
Fine-grained object recognition concerns the identification of the type of an object among a large number of closely related sub-categories. Multisource data analysis, that aims to leverage the complementary spectral, spatial, and structural informat
Externí odkaz:
http://arxiv.org/abs/1901.06403
Fine-grained object recognition that aims to identify the type of an object among a large number of subcategories is an emerging application with the increasing resolution that exposes new details in image data. Traditional fully supervised algorithm
Externí odkaz:
http://arxiv.org/abs/1712.03323
Multi-instance multi-label (MIML) learning is a challenging problem in many aspects. Such learning approaches might be useful for many medical diagnosis applications including breast cancer detection and classification. In this study subset of digiPA
Externí odkaz:
http://arxiv.org/abs/1510.02942
Publikováno v:
In Journal of Visual Communication and Image Representation November 2020 73
Autor:
Aksoy, Selim.
Publikováno v:
Connect to this title online; UW restricted.
Thesis (Ph. D.)--University of Washington, 2001.
Vita. Includes bibliographical references (leaves 245-272).
Vita. Includes bibliographical references (leaves 245-272).
Externí odkaz:
http://hdl.handle.net/1773/5939
Autor:
Gecer, Baris, Aksoy, Selim, Mercan, Ezgi, Shapiro, Linda G., Weaver, Donald L., Elmore, Joann G.
Publikováno v:
In Pattern Recognition December 2018 84:345-356
Publikováno v:
In Pattern Recognition December 2012 45(12):4151-4168
Publikováno v:
In Pattern Recognition July 2012 45(7):2804-2816