Effect of Data Augmentation in the Classification and Validation of Tomato Plant Disease with Deep Learning Methods

The paper discusses disease identification and classification in tomato plants, as well the effect of data augmentation deep learning models. database used here is Tomato plant leaves (TPL) images from PlantVillage Database healthy classes. categories have been chosen depending on their occurrence Indian States. proposed ResNet50, ResNet18, ResNet101 deep-learning model with transfer combined softmax are to identify categorize leaf into or diseases classes dataset. unique combination including noise blur position color makes dataset robust. Two different methods for problem, significant improvement seen accuracy augmented model’s success rate helpful extending support validating a identifying disease. validation models done taken at Krishi Vigyan Kendra Narayangaon, Pune, India. trained outperforms testing 99.99% 95.83%.