TOMATO LEAF DISEASE DETECTION USING INCEPTION V3

Özet

Agriculture is one of our society's most critical fields, and it has been since the Middle Ages. Crop diseases are a major threat to food security, but due to a complete lack of facilities in so many parts of the world, timely detection is difficult. Tomato plants are infected by bacteria and fungi in a number of ways. Early blight and late blight are two fungal diseases that affect plants. Bacterial spot is caused by four Xanthomonas species and can be found wherever tomatoes are grown. Smartphone-assisted disease detection is now possible thanks to a combination of rising global smartphone penetration and recent developments in machine vision made possible by deep learning. To distinguish different tomato leaves, we trained deep convolutional neural network diseases using a public dataset of 54,306 images of diseased and healthy plant leaves collected under controlled conditions and choosing on the images of tomato. The method of training deep learning models on increasingly broad and publicly accessible image datasets points to a direct path toward global crop disease diagnosis aided by technology.