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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

Sandip Dey, Siddhartha Bhattacharyya, Ujjwal Maulik
Copyright: © 2017 |Pages: 39
ISBN13: 9781522507888|ISBN10: 1522507884|EISBN13: 9781522507895
DOI: 10.4018/978-1-5225-0788-8.ch034
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MLA

Dey, Sandip, et al. "Quantum Behaved Swarm Intelligent Techniques for Image Analysis: A Detailed Survey." Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2017, pp. 893-931. https://doi.org/10.4018/978-1-5225-0788-8.ch034

APA

Dey, S., Bhattacharyya, S., & Maulik, U. (2017). Quantum Behaved Swarm Intelligent Techniques for Image Analysis: A Detailed Survey. In I. Management Association (Ed.), Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications (pp. 893-931). IGI Global. https://doi.org/10.4018/978-1-5225-0788-8.ch034

Chicago

Dey, Sandip, Siddhartha Bhattacharyya, and Ujjwal Maulik. "Quantum Behaved Swarm Intelligent Techniques for Image Analysis: A Detailed Survey." In Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 893-931. Hershey, PA: IGI Global, 2017. https://doi.org/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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