A Divide-and-Conquer Genetic Programming Algorithm With Ensembles for Image Classification

Genetic programming (GP) has been applied to feature learning in image classification and achieved promising results. However, one major limitation of existing GP-based methods is the high computational cost, which may limit their applications on large-scale image classification tasks. To address th...

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Veröffentlicht in:	IEEE transactions on evolutionary computation Jg. 25; H. 6; S. 1148 - 1162
Hauptverfasser:	Bi, Ying, Xue, Bing, Zhang, Mengjie
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.12.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Classification Computational efficiency Computing costs Computing time Divide-and-conquer ensemble learning Feature extraction feature learning Genetic algorithms genetic programming (GP) Image classification Knowledge management Knowledge transfer knowledge transfer (KT) Machine learning Sociology Statistics Task analysis Training Training data
ISSN:	1089-778X, 1941-0026
Online-Zugang:	Volltext
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