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{ "item_title" : "Computer Vision Methods for Fast Image Classifi", "item_author" : [" Rafal Scherer "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/03/012/197/3030121976_b.jpg", "price_data" : { "retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Computer Vision Methods for Fast Image Classi&#64257|Rafal Scherer

Computer Vision Methods for Fast Image Classifi : cation and Retrieval

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Overview

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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Details

  • ISBN-13: 9783030121976
  • ISBN-10: 3030121976
  • Publisher: Springer
  • Publish Date: October 2020
  • Dimensions: 9.21 x 6.14 x 0.32 inches
  • Shipping Weight: 0.48 pounds
  • Page Count: 137

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