Computer Vision: Models, Learning + Inference-2010kaiser
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Computer Vision: Models, Learning + Inference-2010kaiser
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This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data. With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build useful vision systems.
Title: Computer Vision: Models, Learning, and Inference
Author: Dr Simon J. D. Prince
Publisher: Cambridge University Press
Year: 2012
ISBN: 978-1107011793
Format: EPUB-PDF
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