Isbn: 9780470976371 - object detection and recognition in digital images: theory and practice (8 Ergebnisse)

Zustand: Poor. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Book contains highlighter markings. In poor condition, suitable as a reading copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1050grams, ISBN:9780470976371.…

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. pp. 516.

Zustand: New. In English.

Zustand: New. Boguslaw Cyganek received his M.Sc. degree in electronics in 1993, then in computer science in 1996 from the AGH University of Science and Technology, Krakow, Poland. He obtained his Ph.D. degree cum laude in 2001 with a thesis on correlation of stereo imag.

Hardcover. Zustand: Brand New. 1st edition. 548 pages. 9.69x6.85x1.18 inches. In Stock.

Zustand: New. This book addresses key problems of computer vision (CV), focusing on the significant issues of object detection, tracking, and recognition in images, which are not found in other CV books. Throughout, the book balances theory, implementation, and case studies in order to provide a complete and accessible treatment of the topic. Num Pages: 548 pages, illustrations. BIC Classification: TJK; TTBM. Category: (P) Professional & Vocational. Dimension: 249 x 179 x 31. Weight in Grams: 1012. . 2013. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.…

Buch. Zustand: Neu. Neuware - Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields.Key features:\* Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications.\* Places an emphasis on tensor and statistical based approaches within object detection and recognition.\* Provides an overview of image clustering and classification methods which includes subspace and kernel based processing, mean shift and Kalman filter, neural networks, and k-means methods.\* Contains numerous case study examples of mainly automotive applications.\* Includes a companion website hosting full C++ implementation, of topics presented in the book as a software library, and an accompanying manual to the software platform. …