Computer Vision Methods for Fast Image Classification and Retrieval

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Application Software, Computer Graphics, General Computing
Cover of the book Computer Vision Methods for Fast Image Classification and Retrieval by Rafał Scherer, Springer International Publishing
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Author: Rafał Scherer ISBN: 9783030121952
Publisher: Springer International Publishing Publication: January 29, 2019
Imprint: Springer Language: English
Author: Rafał Scherer
ISBN: 9783030121952
Publisher: Springer International Publishing
Publication: January 29, 2019
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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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