Accurate recognition of tomato diseases is of great significance for agricultural production. Sufficient and insufficient training data of supervised ...
The proposed research aims to develop more data using a Meta approach, which uses random sampling techniques, passes a few processed images to the generator ...
Accurate recognition of tomato diseases is of great significance for agricultural production. Sufficient and insufficient training data of supervised ...
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Jun 24, 2024 · Deng H., Luo D., Chang Z., Li H., Yang X. RAHC_GAN: A Data Augmentation Method for Tomato Leaf Disease Recognition. Symmetry, 13 (2021), p ...
The proposed data augmentation method can simulate the distribution of tomato leaf diseases and improve the performance of disease recognition, and it may be ...
(2017) Deng et al. (2021) developed their RAHC_GAN to augment tomato leaf disease image data. Their RAHC_GAN used continuous hidden variables added to the ...
The proposed augmentation method performs translation between healthy and diseased leaf images and utilizes attention mechanisms to create images that reflect ...
Sep 19, 2023 · RAHC_GAN: A Data Augmentation Method for Tomato Leaf Disease Recognition. ... Data Augmentation Method for Tomato Leaf Disease Recognition ...
[26] proposed an RHAC_GAN model that improves ACGAN (Auxiliary Classifier GAN) to solve the problem of tomato disease data augmentation. RHAC_GAN aims to solve ...
The results demonstrate that the proposed data augmentation method represents a new approach to overcoming the overfitting problem in disease identification ...