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Computer Vision Methods for Fast Image Classification and Retrieval
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| Titel: | Computer Vision Methods for Fast Image Classification and Retrieval/ by Rafał Scherer |
| Format: | E-Book |
| Sprache: | Englisch |
| veröffentlicht: |
Cham
Springer International Publishing
2020
|
| Gesamtaufnahme: |
Studies in Computational Intelligence Springer eBook Collection SpringerLink |
| Schlagwörter: | |
| Quelle: | Verbunddaten SWB |
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| 520 | |a 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 | ||
| 520 | |a 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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| 650 | 0 | |a Computational Intelligence | |
| 650 | 0 | |a Optical data processing. | |
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| author | Scherer, Rafał |
| author_facet | Scherer, Rafał |
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| author_sort | Scherer, Rafał |
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| contents | 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, 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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| local_heading_facet_dezwi2 | Engineering, Computer vision, Computational Intelligence, Optical data processing. |
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| physical | Online-Ressource (IX, 137 p. 85 illus., 55 illus. in color, online resource) |
| publishDate | 2020 |
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| spelling | Scherer, Rafał VerfasserIn aut, Computer Vision Methods for Fast Image Classification and Retrieval by Rafał Scherer, Cham Springer International Publishing 2020, Online-Ressource (IX, 137 p. 85 illus., 55 illus. in color, online resource), Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, Studies in Computational Intelligence 821, Springer eBook Collection, SpringerLink Bücher, 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, 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, Springer eBook Collection. Intelligent Technologies and Robotics, Engineering, Computer vision, Computational Intelligence, Optical data processing., 9783030121945, 9783030121969, 9783030121976, Erscheint auch als Druck-Ausgabe 978-3-030-12194-5, Printed edition 9783030121945, Printed edition 9783030121969, Printed edition 9783030121976, https://doi.org/10.1007/978-3-030-12195-2 X:SPRINGER Verlag lizenzpflichtig Volltext, http://dx.doi.org/10.1007/978-3-030-12195-2 Resolving-System Volltext, https://swbplus.bsz-bw.de/bsz516884042cov.jpg V:DE-576 X:Springer image/jpeg 20190228140129 Cover, https://doi.org/10.1007/978-3-030-12195-2 DE-Ch1, DE-Ch1 epn:3551102716 2019-11-28T16:29:32Z, https://doi.org/10.1007/978-3-030-12195-2 DE-Zwi2, DE-Zwi2 epn:3546604156 2019-11-22T17:06:14Z |
| spellingShingle | Scherer, Rafał, Computer Vision Methods for Fast Image Classification and Retrieval, 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, 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, Engineering, Computer vision, Computational Intelligence, Optical data processing. |
| swb_id_str | 516884042 |
| title | Computer Vision Methods for Fast Image Classification and Retrieval |
| title_auth | Computer Vision Methods for Fast Image Classification and Retrieval |
| title_full | Computer Vision Methods for Fast Image Classification and Retrieval by Rafał Scherer |
| title_fullStr | Computer Vision Methods for Fast Image Classification and Retrieval by Rafał Scherer |
| title_full_unstemmed | Computer Vision Methods for Fast Image Classification and Retrieval by Rafał Scherer |
| title_short | Computer Vision Methods for Fast Image Classification and Retrieval |
| title_sort | computer vision methods for fast image classification and retrieval |
| title_unstemmed | Computer Vision Methods for Fast Image Classification and Retrieval |
| topic | Engineering, Computer vision, Computational Intelligence, Optical data processing. |
| topic_facet | Engineering, Computer vision, Computational Intelligence, Optical data processing. |
| url | https://doi.org/10.1007/978-3-030-12195-2, http://dx.doi.org/10.1007/978-3-030-12195-2, https://swbplus.bsz-bw.de/bsz516884042cov.jpg |