Learning features for data-efficient image classification via improved decomposition-based multi-objective genetic programming

doi:10.1016/j.swevo.2026.102430

Learning features for data-efficient image classification via improved decomposition-based multi-objective genetic programming

2026-06-16

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DOI：10.1016/j.swevo.2026.102430

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• Maximizes accuracy using Rademacher complexity regularization. • Introduces an adaptive global replacement strategy. • Develops improved decomposition-based MOGP for feature learning in image classification.

Learning features for data-efficient image classification via improved decomposition-based multi-objective genetic programming

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