M
Mingwei Wang
Researcher at Wuhan University
Publications - 32
Citations - 536
Mingwei Wang is an academic researcher from Wuhan University. The author has contributed to research in topics: Computer science & Cuckoo search. The author has an hindex of 9, co-authored 21 publications receiving 387 citations. Previous affiliations of Mingwei Wang include Hubei University of Technology.
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A feature selection method based on modified binary coded ant colony optimization algorithm
TL;DR: Results show that the proposed feature selection approach based on a modified binary coded ant colony optimization algorithm (MBACO) combined with genetic algorithm (GA) is robust, adaptive and exhibits the better performance than other methods involved in the paper.
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Remote sensing image classification based on the optimal support vector machine and modified binary coded ant colony optimization algorithm
TL;DR: A remote sensing image classification technique based on the optimal SVM is proposed, in which the parameters of SVM and feature selection are handled integrally by a modified coded ant colony optimization algorithm combined with genetic algorithm.
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Fuzzy entropy based optimal thresholding using bat algorithm
TL;DR: It is demonstrated that the proposed thresholding method is robust, adaptive, encouraging on the score of CPU time and exhibits the better performance than other methods involved in the paper in terms of objective function values.
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A band selection method for airborne hyperspectral image based on chaotic binary coded gravitational search algorithm
TL;DR: A novel band selection method based on a chaotic binary coded gravitational search algorithm (CBGSA) is proposed to reduce the dimensionality of airborne hyperspectral images and is compared with some existing techniques such as Relief-F algorithm, minimum Redundancy Maximum Relevance (mRMR) criterion, and the optimum index (OI) criterion for a comprehensive comparison.
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An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm
TL;DR: A new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively is presented.