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- W2103182380 abstract "In the face gender recognition system, in addition to want to obtain high recognition rate, but also want to be able to achieve recognition quickly which relates to multi-objective optimization problem. In this paper, we proposed an adaptive face gender recognition method based on NSGA-II which can make recognition performance and running time optimal at the same time. In our method, we use CS to extract features and Extreme Learning Machine (ELM) to achieve features recognition. Then, NSGA-II is used to optimize the method. Experimental results show that the proposed method using NSGA-II solving optimization problems can obtain evenly distributed Pareto optimal solution set at a fast convergence in the solution space which demonstrates feasibility and effectiveness of using NSGA-II to solve multi-objective face gender recognition problems." @default.
- W2103182380 created "2016-06-24" @default.
- W2103182380 creator A5066085701 @default.
- W2103182380 date "2015-03-01" @default.
- W2103182380 modified "2023-09-27" @default.
- W2103182380 title "Adaptive Face Gender Recognition Based on NSGA-II and Compressive Sensing" @default.
- W2103182380 cites W2044714466 @default.
- W2103182380 cites W2126105956 @default.
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- W2103182380 doi "https://doi.org/10.4028/www.scientific.net/amm.738-739.586" @default.
- W2103182380 hasPublicationYear "2015" @default.
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