Grape Leaf Diseases Classification using Convolutional Neural Network

Most of the grape plant diseases are severe and spread rapidly. The grape plant diseases start on the leaf and then spread to stem, fruit, and root. It has problems with time-consuming and lacking knowledge for farmers in remote areas to classify grapes leaf diseases because of limited access to human experts in developing countries. In recent research, grape leaf diseases are classified with fine-tuning VGG16 Network. But the classification was not received good accuracy results with VGG16 Architecture. This system proposes transfer learning via fine-tuning of VGG16 network, one of CNN Architecture, to classify diseases on grape leaf The system used Global Average Pooling (GAP) layer instead of VGG16's two fully connected layers before final classification SoftMax layer to improve accuracy result of fine-tuning VGG16 for grape leaf diseases classification. The proposed system mainly analyzed healthy leaves and five leaves diseases, named anthracnose, downy mildew, black measles, isariopsis leaf spot, nutrient insufficient, on 6000 images dataset of Myanmar Grapevine Yard. The proposed system compared the accuracy with VGG16 using fully connected layers and VGG16 using SVM classifier. The proposed system outperformed with 98.4% accuracy than others.