Automatically extracting features for face classification using multi-objective genetic programming
| Autor: | Mengjie Zhang, Ying Bi, Bing Xue |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry Feature extraction Sorting Genetic programming Pattern recognition 0102 computer and information sciences 02 engineering and technology 01 natural sciences Multi objective genetic programming 010201 computation theory & mathematics Face (geometry) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Baseline (configuration management) business |
| Zdroj: | GECCO Companion |
| DOI: | 10.26686/wgtn.13884935.v1 |
| Popis: | © 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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