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Quantum Behaved Swarm Intelligent Techniques for Image Analysis: A Detailed Survey

Quantum Behaved Swarm Intelligent Techniques for Image Analysis: A Detailed Survey
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Author(s): Sandip Dey (Camellia Institute of Technology, India), Siddhartha Bhattacharyya (RCC Institute of Information Technology, India) and Ujjwal Maulik (Jadavpur University, India)
Copyright: 2017
Pages: 39
Source title: Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-0788-8.ch034

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Abstract

In this chapter, an exhaustive survey of quantum behaved techniques on swarm intelligent is presented. The techniques have been categorized into different classes, and in conclusion, a comparison is made according to the benefits of the approaches taken for review. The above-mentioned techniques are classified based on the information they exploit, for instance, neural network related, meta-heuristic and evolutionary algorithm related, and other distinguished approaches are considered. Neural Network-Based Approaches exhibit a few brain-like activities, which are programmatically complicated, for instance, learning, optimization, etc. Meta-Heuristic Approaches update solution generation-wise for optimization, and the approaches differ based on the problem definition.

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