AUTOMATIC PREDICTION OF PLANT LEAF DISEASES USING DEEP LEARNING MODELS: A REVIEW

with the development of automated technology in agriculture and food production, there are still some phases that need an enhancement. One of such necessary phases is the detection of leaf diseases without the requirement of any manual support. Various diseases like blights, leaf spots and other bacterial and fungal infections are found in plant leaves. These defects bring a tremendous negative influence on the quality and quantity of crop yield. In order to prevent the plant leaves from getting destroyed, a better solution is needed to protect them from the beginning stage. Several works have been proposed to recognize and plant diseases. In this paper, a review is conducted to analyze the results of works based on detection of plant leaf diseases using machine learning and deep learning models. Based on the results, a transfer learning model with better performance is to be implemented along with the Jetson Nano kit for faster and efficient processing. As a result, transfer learning model could classify the images of affected plant leaves based on their defects. Location parameters could also be obtained along with the type of disease for early diagnosis of those diseases.