Computer Vision: A Modern Approach

Forsyth, David A.; Ponce, Jean

ISBN 10: 0130851981 ISBN 13: 9780130851987
Edité par Prentice Hall, 2002
Ancien(s) ou d'occasion Couverture rigide

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Description :

Book is in good condition and may include underlining highlighting and minimal wear. The book can also include "From the library of" labels. May not contain miscellaneous items toys, dvds, etc. . We offer 100% money back guarantee and 24 7 customer service. N° de réf. du vendeur ZEV.0130851981.G

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Synopsis :

Appropriate for upper-division undergraduate- and graduate-level courses in computer vision found in departments of Computer Science, Computer Engineering and Electrical Engineering.

This long anticipated book is the most complete treatment of modern computer vision methods by two of the leading authorities in the field. This accessible presentation gives both a general view of the entire computer vision enterprise and also offers sufficient detail for students to be able to build useful applications. Students will learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods.

À propos de l'auteur:

David A. Forsyth received the D.Phil. degree in computer science from Oxford University. He is currently a Professor in the Computer Science Division at the University of California at Berkeley. He has co-authored over eighty technical papers on computer vision, computer graphics and machine learning and has co-edited two books.

Jean Ponce received the Ph.D. degree in Computer Science from the University of Paris Orsay. He is currently a Professor in the Department of Computer Science and the Beckman Institute at the University of Illinois at Urbana Champaign. Professor Ponce has written over a hundred conference and journal papers and co-edited two books on a range of subjects including computer vision and robotics.

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Détails bibliographiques

Titre : Computer Vision: A Modern Approach
Éditeur : Prentice Hall
Date d'édition : 2002
Reliure : Couverture rigide
Etat : good

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