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Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval (Texts in Computer Science) 1st ed Springer
Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval (Texts in Computer Science) 1st ed Springer Springer  

Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval (Texts in Computer Science) 1st ed
مبانی داده کاوی تصویر

کد کتاب 186631

Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval (Texts in Computer Science) 1st ed

کتاب مبانی داده کاوی تصویر

افست = اورجینال
چاپ تمام رنگی

کاغذ 80 گرمی اندونزی
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خرید Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval (Texts in Computer Science) 1st ed

دارای 18% تخفیف  

Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval (Texts in Computer Science) 1st ed

کتاب مبانی داده کاوی تصویر

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 mathematical models 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 Networks, and Decision Trees; discusses techniques for indexing, image ranking, and image presentation, along with image database visualization 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 mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics 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 computing.

Product details

  • Paperback | 314 pages
  • 155 x 235 x 18.29mm | 534g
  • Cham, Switzerland
  • English
  • 1st ed. 2019
  • 117 Illustrations, color; 85 Illustrations, black and white; XXXI, 314 p. 202 illus., 117 illus. in color.
  • 3030179915
  • 9783030179915