Isbn: 9781032727431 - handbook of texture analysis: ai-based medical imaging applications (16 risultati)

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  • Lingua: Inglese

    Editore: CRC Press, 2025

    1032727438 / 9781032727431

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  • Lingua: Inglese

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    Paperback. Condizione: Brand New. 270 pages. 9.18x6.12x9.21 inches. In Stock.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, London, 2025

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    Paperback. Condizione: new. Paperback. The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book:Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methodsCovers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformationDescribes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentationIs aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineeringThis is an essential reference for those looking to advance their understanding in this applied and emergent field. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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    Paperback. Condizione: new. Paperback. The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book:Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methodsCovers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformationDescribes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentationIs aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineeringThis is an essential reference for those looking to advance their understanding in this applied and emergent field. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, London, 2025

    1032727438 / 9781032727431

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    Paperback. Condizione: new. Paperback. The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book:Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methodsCovers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformationDescribes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentationIs aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineeringThis is an essential reference for those looking to advance their understanding in this applied and emergent field. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

  • Lingua: Inglese

    Editore: CRC Press, 2025

    1032727438 / 9781032727431

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    Taschenbuch. Condizione: Neu. Handbook of Texture Analysis | AI-Based Medical Imaging Applications | Ayman El-Baz (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | CRC Press | EAN 9781032727431 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.