Computational Learning For Adaptive Computer Vision

by Bhanu, Bir; DAS, SUBHODEV

• ISBN13: 9780387237039
• ISBN10: 0387237038
• Format: Hardcover
• Copyright: 2018-04-15
• Publisher: Springer Verlag

Summary

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.

Table of Contents

Introduction

Learning as a Discipline

Basic Paradigms of Learning

Selection of Learning Paradigms and Designing Practical Learning Systems for Vision

Learning Applied to Low-Level Vision

Learning Applied to Intermediate-Level Vision

Learning Applied to High-Level Vision

Learning Integrated Multi-Level Vision

Learning Applied to Integrating Vision and Action

Applications

Summary

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