2024
DOI: 10.1038/s41598-024-59918-3
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SM-CycleGAN: crop image data enhancement method based on self-attention mechanism CycleGAN

Dian Liu,
Yang Cao,
Jing Yang
et al.

Abstract: Crop disease detection and crop baking stage judgement require large image data to improve accuracy. However, the existing crop disease image datasets have high asymmetry, and the poor baking environment leads to image acquisition difficulties and colour distortion. Therefore, we explore the potential of the self-attention mechanism on crop image datasets and propose an innovative crop image data-enhancement method for recurrent generative adversarial networks (GANs) fused with the self-attention mechanism to … Show more

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