Enhancing Tomato Crop Health: InceptionV3-Based Disease Classification

Globally, potatoes and tomatoes are the most widely produced crops. Antioxidant qualities in tomatoes shield cells from free radical damage. Additionally, it can shield the body against sunburn and cancer. Tomatoes are included in the fundamental diet of humans. However, several diseases affect a plant's health and hinder its ability to develop. Identifying tomato plant diseases quickly and accurately is essential to raising the plants' long-term agricultural yield. Physical alterations in the tomato plant's leaves can be used to identify diseases. Early detection of plant leaf diseases is good for the Indian economy. The tomato leaf disease categorization in this study was completed using the Inception V3 model. Two different batch sizes are utilized with epoch 20. Firstly, batch size 32 is applied at epoch 20 and the calculated results are that loss is 0.4156 and 0.5585 during the training and validation phases respectively. Similarly at the same time accuracy is 0.9009 and 0.8796 during the training and validation phases respectively. Thereafter, batch size 64 is applied at epoch 20 and the calculated results are that loss is 0.3324 and 0.4874 during the training and validation phases respectively. Similarly at the same time accuracy is 0.9084 and 0.8925 during the training and validation phases respectively. Lastly, it has been observed that the model best performed with batch size 64 and epoch 20.