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Automatically extracting features for face classification using multi-objective genetic programming

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conference contribution
posted on 11.02.2021, 02:24 by Ying Bi, Bing Xue, Mengjie 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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Preferred citation

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/10.1145/3377929.3389989

Conference name

GECCO '20: Genetic and Evolutionary Computation Conference

Title of proceedings

GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

Publication or Presentation Year

08/07/2020

Pagination

117-118

Publisher

ACM

Publication status

Published

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