Image segmentation by minimum cross entropy using evolutionary methods
- 30 August 2017
- journal article
- research article
- Published by Springer Science and Business Media LLC in Soft Computing
- Vol. 23 (2), 431-450
- https://doi.org/10.1007/s00500-017-2794-1
Abstract
No abstract availableKeywords
This publication has 45 references indexed in Scilit:
- Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropyExpert Systems with Applications, 2014
- Exploring effect of segmentation scale on orient-based crop identification using HJ CCD data in Northeast ChinaIOP Conference Series: Earth and Environmental Science, 2014
- Tsallis entropy based optimal multilevel thresholding using cuckoo search algorithmSwarm and Evolutionary Computation, 2013
- A study on particle swarm optimization and artificial bee colony algorithms for multilevel thresholdingApplied Soft Computing, 2013
- A study on the use of non-parametric tests for analyzing the evolutionary algorithms’ behaviour: a case study on the CEC’2005 Special Session on Real Parameter OptimizationJournal of Heuristics, 2008
- On the Convergence of a Population-Based Global Optimization AlgorithmJournal of Global Optimization, 2004
- An Electromagnetism-like Mechanism for Global OptimizationJournal of Global Optimization, 2003
- Learning and optimization using the clonal selection principleIEEE Transactions on Evolutionary Computation, 2002
- Ant system: optimization by a colony of cooperating agentsIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1996
- Learning with genetic algorithms: An overviewMachine Learning, 1988