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Record Nr. |
UNINA9910483939403321 |
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Autore |
Scherer Rafał |
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Titolo |
Computer Vision Methods for Fast Image Classification and Retrieval / / by Rafał Scherer |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (IX, 137 p. 85 illus., 55 illus. in color.) |
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Collana |
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Studies in Computational Intelligence, , 1860-9503 ; ; 821 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Computer vision |
Computational Intelligence |
Computer Vision |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Preface -- Chapter 1. Introduction -- Chapter 2. Feature Detection -- Chapter 3. Image Indexing Techniques -- Chapter 4. Novel Methods for Image Description -- Chapter 5. Image Retrieval and Classification in Relational Databases etc. |
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Sommario/riassunto |
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The book presents selected methods for accelerating image retrieval and classification in large collections of images using what are referred to as ‘hand-crafted features.’ It introduces readers to novel rapid image description methods based on local and global features, as well as several techniques for comparing images. Developing content-based image comparison, retrieval and classification methods that simulate human visual perception is an arduous and complex process. The book’s main focus is on the application of these methods in a relational database context. The methods presented are suitable for both general-type and medical images. Offering a valuable textbook for upper-level undergraduate or graduate-level courses on computer science or engineering, as well as a guide for computer vision researchers, the book focuses on techniques that work under real-world large-dataset conditions. |
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