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Automatically extracting features for face classification using multi-objective genetic programming
conference contribution
posted on 2021-02-11, 02:24 authored by Ying Bi, Bing XueBing Xue, Mengjie ZhangMengjie Zhang© 2020 Owner/Author. This paper proposes a new multi-objective feature extraction algorithm using genetic programming (GP) for face classification. The new multi-objective GP-based feature extraction algorithm with the idea of non-dominated sorting, which aims to maximise the objective of the classification accuracy and minimise the objective of the number of extracted features. The results show that the proposed algorithm achieves significantly better performance than the baseline methods on two different face classification datasets.
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Bi, Y., Xue, B. & Zhang, M. (2020, July). Automatically extracting features for face classification using multi-objective genetic programming. In GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion GECCO '20: Genetic and Evolutionary Computation Conference (pp. 117-118). ACM. https://doi.org/10.1145/3377929.3389989Publisher DOI
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GECCO '20: Genetic and Evolutionary Computation ConferenceTitle of proceedings
GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference CompanionPublication or Presentation Year
2020-07-08Pagination
117-118Publisher
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