"Advances in Object Recognition Systems" ed. by Ioannis Kypraios

This book presents recent advances towards achieving fully-robust object recognition. With the recent technological advancements object recognition becomes widely popular with existing applications in medicine for the study of human learning and memory, space science and remote sensing for image analysis, mobile computing and augmented reality, semiconductors industry, robotics and autonomous mobile navigation, public safety and urban management solutions and many more others. This book is a "must-read" for everyone with a core or wider interest in this "hot" area of cutting-edge research.

The relation and importance of object recognition in the cognitive processes of humans and animals is described as well as how human- and animal-like cognitive processes can be used for the design of biologically-inspired object recognition systems. Colour processing is discussed in the development of fully-robust object recognition systems. Examples of two main categories of object recognition systems, the optical correlators and pure artificial neural network architectures, are given. Finally, two examples of object recognition's applications are described in details.

Contents
Preface
Section 1 Cognition, and Biologically-Inspired Systems
1 Neural Basis of Object Recognition
2 Spontaneous Object Recognition in Animals: ATest of Episodic Memory
3 Performance Analysis of the Modified-Hybrid Optical Neural Network Object Recognition System Within Cluttered Scenes
Section 2 Colour Processing
4 The Contribution of Color to Object Recognition
Section 3 Optical Correlators, and Artificial Neural Networks
5 Advances in Adaptive Composite Filters for Object Recognition
6 The Use of Contour, Shape and Form in an Integrated Neural Approach for Object Recognition
Section 4 Applications
7 Automatic Coin Classification and Identification
8 Non-Rigid Objects Recognition: Automatic Human Action Recognition in Video Sequences

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