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arXiv AI By Hicham El Akhal, Abderrahim Waga, Aissa Ben Yahya, Abdelbaki El Belrhiti El Alaoui

Enhancing Deep Learning Model Performance through Data Generation Strategies: Classification of Olive Tree Diseases

Read the original on arXiv AI →

The paper proposes a comprehensive data generation strategy to improve deep learning performance in classifying olive tree diseases. It combines traditional augmentation, CutMix, MixUp, and DCGAN-generated synthetic images to address data scarcity and class imbalance. Experiments with EfficientNetV2B0 show significant accuracy gains across three distribution scenarios, underscoring the importance of data diversity and balance.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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