Bir Bhanu, Subhodev Das

Computational Learning for Adaptive Computer Vision

• Gebundenes Buch

Produktbeschreibung

The goal of computer vision (CV) research is to provide computers with human-like perception capabilities so that they can sense the environment, understand the sensed data, take appropriate actions, and learn from this experience in order to enhance future performance. The field has evolved from the application of classical pattern recognition and image processing methods to advanced techniques in image understanding, like model-based and knowledge-based vision.

In recent years, there has been an increased demand for computer vision systems to address "real-world" applications, such as navigation, target recognition, manufacturing, photointerpretation, remote sensing, etc. This unique monograph details the way machine learning, a field concerned with the temporal improvement of computer algorithms and systems, can help create robust, flexible vision techniques for optimal functioning in real-world scenarios. Enriched by many concrete examples and illustrations, it is an indispensable reference for industry engineers and academics working in machine vision and AI.

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Produktdetails

• Verlag: Springer / Springer US / Springer, Berlin
• Artikelnr. des Verlages: 11339397, 978-0-387-23703-9
• 1st ed. 2018
• Seitenzahl: 505
• Erscheinungstermin: 13. Mai 2016
• Englisch
• Abmessung: 229mm x 152mm
• ISBN-13: 9780387237039
• ISBN-10: 0387237038
• Artikelnr.: 22072874

Inhaltsangabe

1. Introduction

2. Learning as a Discipline

3. Basic Paradigms of Learning

4. Selection of Learning Paradigms and Designing Practical Learning Systems for Vision

5. Learning Applied to Low-Level Vision

6. Learning Applied to Intermediate-Level Vision

7. Learning Applied to High-Level Vision

8. Learning Integrated Multi-Level Vision

9. Learning Applied to Integrating Vision and Action

10. Applications

11. Summary