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Visual Object Recognition (Synthesis Lectures on Artificial Intelligence and Machine Learning) [9783031004254]

Paperback
SKU: 9783031004254
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Format Lightweight and affordable. Perfect for student groups and classrooms, and a versatile option for corporate trainings, team reads, or large-scale events.

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Overview

The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: Specific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions

The book, Visual Object Recognition (Synthesis Lectures on Artificial Intelligence and Machine Learning) [Bulk, Wholesale, Quantity] ISBN#9783031004254 in Paperback by Kristen Grauman, Bastian Leibe may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.

Details

Author:
Kristen Grauman Bastian Leibe
Format:
Paperback
Publication Date:
04/19/2011
ISBN-13:
9783031004254
Pages:
163
Publisher:
Springer Nature Switzerland

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