Image processing and machine learning [2 Vols.]
By: Cuevas, Erik.
Contributor(s): Rodríguez, Alma Nayeli.
Publisher: Boca Raton CRC Press 2024Description: Various pagings.ISBN: 9781032234588, 9781032660325.Subject(s): Image processing | Machine learningDDC classification: 006.6 | C894i| Item type | Current location | Collection | Call number | Vol info | Status | Date due | Barcode | Item holds |
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Books
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PK Kelkar Library, IIT Kanpur | On Display | 006.6 C894i v.1 (Browse shelf) | v.1 Foundations of image processing | Available | A186670 | ||
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Books
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PK Kelkar Library, IIT Kanpur | On Display | 006.6 C894i v.2 (Browse shelf) | v.2. Advanced topics in image analysis and machine learning | Available | A186671 |
Browsing PK Kelkar Library, IIT Kanpur Shelves , Collection code: On Display Close shelf browser
| 006.6 C894i v.1 Image processing and machine learning [2 Vols.] | 006.6 C894i v.2 Image processing and machine learning [2 Vols.] | 006.6 Z61t 3D computer vision | 338 Op7 Optimization in industry | 543.57 R141 Raman spectroscopy |
v.1. Foundations of image processing, pg. xiii, 209p., 9781032234588: A186670; v.2.Advanced topics in image analysis and machine learning, pg. xiv, 223p., 9781032660325: A186671
Vol.1. Image processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches.
Divided into two volumes, this first installment explores the fundamental concepts and techniques in image processing, starting with pixel operations and their properties and exploring spatial filtering, edge detection, image segmentation, corner detection, and geometric transformations. It provides a solid foundation for readers interested in understanding the core principles and practical applications of image processing, establishing the essential groundwork necessary for further explorations covered in Volume 2.
Written with instructors and students of image processing in mind, this book’s intuitive organization also contains appeal for app developers and engineers.
Vol.2. Image processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches.
Divided into two volumes, this second installment explores the more advanced concepts and techniques in image processing, including morphological filters, color image processing, image matching, feature-based segmentation utilizing the mean shift algorithm, and the application of singular value decomposition for image compression. This second volume also incorporates several important machine learning techniques applied to image processing, building on the foundational knowledge introduced in Volume 1.
Written with instructors and students of image processing in mind, this book’s intuitive organization also contains appeal for app developers and engineers.
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