Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval

Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval Front Cover
0 Reviews
2019-07-16
314 pages

Book Description

This reader-friendly textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical and algorithms, utilizing data from real-world examples and experiments.

Topics and features: describes the essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms; reviews a varied range of state-of-the-art models, algorithms, and procedures for image mining; emphasizes how to deal with real image data for practical image mining; highlights how such features as color, texture, and shape can be mined or extracted from images for image representation; presents four powerful approaches for classifying image data, namely, Bayesian classification, Support Vector Machines, Neural , and Decision Trees; discusses techniques for indexing, image ranking, and image presentation, along with image database methods; provides self-test exercises with instructions or Matlab code, as well as review summaries at the end of each chapter.

This easy-to-follow work illuminates how concepts from fundamental and advanced can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of .

Book Details

  • Title: Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval
  • Author:
  • Length: 314 pages
  • Edition: 1st ed. 2019
  • Language: English
  • Publisher:
  • Publication Date: 2019-07-16
  • ISBN-10: 3030179885
  • ISBN-13: 9783030179885
Download LinkFormatSize (MB)Upload Date
Direct download (Recommended!)True PDF12.705/15/2019
Download from NitroFlareTrue PDF12.705/15/2019
Download from UsersCloudTrue PDF12.705/15/2019
How to Download? Report Dead Links & Get a Copy

Leave a Reply