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About this paper
Saundarya Subramaniam, Shalini Majumdar, Shantanu Nadar, Kaustubh Kulkarni
The authors compare five leaf-image classifiers for crop disease recognition on a combined dataset of more than 130,000 images, including a custom CNN and established architectures. They resize and normalize images and apply augmentation. Validation accuracy, the proportion of validation examples classified correctly, is 97.10% for EfficientNetB0 versus 95.76% for the custom CNN; no field evaluation is reported.
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