High-Order Models in Semantic Image Segmentation reviews recent developments in optimization-based methods for image segmentation, presenting several geometric and mathematical models that underlie a broad class of recent segmentation techniques. Focusing on impactful algorithms in the computer vision community in the last 10 years, the book includes sections on graph-theoretic and continuous relaxation techniques, which can compute globally optimal solutions for many problems. The book provides a practical and accessible introduction to these state-of -the-art segmentation techniques that is ideal for academics, industry researchers, and graduate students in computer vision, machine learning and medical imaging. – Gives an intuitive and conceptual understanding of this mathematically involved subject by using a large number of graphical illustrations- Provides the right amount of knowledge to apply sophisticated techniques for a wide range of new applications- Contains numerous tables that compare different algorithms, facilitating the appropriate choice of algorithm for the intended application- Presents an array of practical applications in computer vision and medical imaging- Includes code for many of the algorithms that is available on the book’s companion website
Ismail Ben Ayed
High-Order Models in Semantic Image Segmentation [EPUB ebook]
High-Order Models in Semantic Image Segmentation [EPUB ebook]
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Idioma Inglés ● Formato EPUB ● ISBN 9780128092293 ● Editorial Elsevier Science ● Publicado 2023 ● Descargable 3 veces ● Divisa EUR ● ID 6207131 ● Protección de copia Adobe DRM
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