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Paper Title
Application of Swarm Intelligence In Image Classification
  Ambica Verma,  Dr. Ramandeep Singh

Bio-Inspired computing is the subset of Nature-Inspired computing. In this study, Bacterial Foraging optimization was hybridized with Ant Colony Optimization and a new technique Hybrid Bacterial Foraging Optimization to extract natural terrain features was proposed. The ideal solutions achieved by proposed Hybrid Bacterial Foraging Optimization algorithms are much better when compared with the solutions obtained by Bacterial Foraging Optimization algorithm for well-known test problems of unlike sizes. From the implementation of this research work, it could be pragmatic that the proposed Hybrid Bacterial Foraging Optimization was better than Bacterial Foraging Optimization algorithm in extraction of natural terrain features. Hybrid Bacterial Foraging Optimization is used to implement image classification using natural terrain feature extraction.

Keywords- Ant Colony Optimization (ACO), Bacterial Foraging Optimization (BFO), Swarm Intelligence (SI), Natural terrain features, Hybrid Bacterial Foraging Optimization (HBFO).
Publication Details
Unique Identification Number - IJEDR1702069
Page Number(s) - 400-403
Pubished in - Volume 5 | Issue 2 | April 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Ambica Verma,  Dr. Ramandeep Singh,   "Application of Swarm Intelligence In Image Classification", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 2, pp.400-403, April 2017, Available at :http://www.ijedr.org/papers/IJEDR1702069.pdf
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