{"product_id":"fundamentals-of-image-data-mining-analysis-features-classification-and-retrieval-paperback","title":"Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eDengsheng Zhang\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e1. Fourier Transform.- 2. Windowed Fourier Transform.- 3. Wavelet Transform.- 4. Color Feature Extraction.- 5. Texture Feature Extraction.- 6. Shape Representation.- 7. Bayesian Classification.- Support Vector Machines.- 8. Artificial Neural Networks.- 9. Image Annotation with Decision Trees.-10. Image Indexing.- 11. Image Ranking.- 12. Image Presentation.- 13. Appendix.\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis unique and useful 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. \u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e\u003cb\u003eTopics and features: \u003c\/b\u003e \u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDescribes essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms\u003c\/li\u003e\n\u003cli\u003eDevelops \u003ci\u003emany new exercises\u003c\/i\u003e (most with MATLAB code and instructions)\u003c\/li\u003e\n\u003cli\u003eIncludes review summaries at the end of each chapter\u003c\/li\u003e\n\u003cli\u003eAnalyses state-of-the-art models, algorithms, and procedures for image mining\u003c\/li\u003e\n\u003cli\u003eIntegrates \u003ci\u003enew sections\u003c\/i\u003e on pre-processing, discrete cosine transform, and statistical inference and testing\u003c\/li\u003e\n\u003cli\u003eDemonstrates how features like color, texture, and shape can be mined or extracted for image representation\u003c\/li\u003e\n\u003cli\u003eApplies powerful classification approaches: Bayesian classification, support vector machines, neural networks, and decision trees\u003c\/li\u003e\n\u003cli\u003eImplements imaging techniques for indexing, ranking, and presentation, as well as database visualization\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003eThis easy-to-follow, award-winning book 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.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eDr. Dengsheng Zhang\u003c\/b\u003e is Senior Lecturer in the School of Engineering, Information Technology and Physical Sciences at Federation University Australia and a Guest Professor of Xi'an University of Posts \u0026amp; Telecommunications, China. He is on the list of Top 2% Scientists in the World ranked by Stanford University. Dr Zhang was the Textbook \u0026amp; Academic Authors Association's winner of their 2020 Most Promising New Textbook Award, with the judges noting: \u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e \u003cp\u003e\"\u003ci\u003eFundamentals of Image Data Mining\u003c\/i\u003e provides excellent coverage of current algorithms and techniques in image analysis. It does this using a progression of essential and novel image processing tools that give students an in-depth understanding of how the tools fit together and how to apply them to problems.\"\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 363\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.82 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e June 27, 2022\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47212629262585,"sku":"9783030692537","price":89.08,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/QldFY0Y1by9aWThuKzhORlpITTVCZz09.webp?v=1768094771","url":"https:\/\/bookscloud.io\/products\/fundamentals-of-image-data-mining-analysis-features-classification-and-retrieval-paperback","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}