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What is BDSONN

Handbook of Research on Swarm Intelligence in Engineering
This architecture is a three-layer network structure assisted by bi-directional propagation of network states for self-supervised organization of input information.
Published in Chapter:
Quantum Inspired Swarm Optimization for Multi-Level Image Segmentation Using BDSONN Architecture
Subhadip Chandra (Camellia Institute of Technology, India) and Siddhartha Bhattacharyya (RCC Institute of Information Technology, India)
Copyright: © 2015 |Pages: 41
DOI: 10.4018/978-1-4666-8291-7.ch009
Abstract
This chapter is intended to propose a quantum inspired self-supervised image segmentation method by quantum-inspired particle swarm optimization algorithm and quantum-inspired ant colony optimization algorithm, based on optimized MUSIG (OptiMUSIG) activation function with a bidirectional self-organizing neural network architecture to segment multi-level grayscale images. The proposed quantum-inspired swarm optimization-based methods are applied on three standard grayscale images. The performances of the proposed methods are demonstrated in comparison with their conventional counterparts. Experimental results are reported in terms of fitness value, computational time, and class boundaries for both methods. It has been noticed that the quantum-inspired meta-heuristic method is superior in terms of computational time in comparison to its conventional counterpart.
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