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The paper presents Selective VGG19-Net, a deep learning model designed for the classification of apple and citrus leaf diseases, achieving high accuracy rates of 99.83% and 98.03%, respectively. This model employs selective layer freezing and convolutional-pooling depth extensions to enhance feature representation and mitigate overfitting, particularly beneficial for small agricultural datasets. The study highlights the potential of advanced AI techniques in improving early disease detection in agriculture,

Author

shinyrm

Language

EN