Identification of Rice Plant Disease Using Convolution Neural Network Inception V3 and Squeeze Net Models - Ujawe , Priya; Gupta , Poonam; Waghmare, Surendra (International Journal of Intelligent Systems and Applications in Engineering, 2023)
Agriculture is the most important factor of every country. Crop disease is one of the reasons to reduce the crop yield. So detect the crop disease at early age yield help to improve crop production. In India, Rice is one of the important foods. Different products are made from rice, so it also helps to improve economy of country. But due to different disease found on rice plant, causes the loss of production, which also affects the economy of country. Mostly bacterial blight, blast and brownspot are the diseases found on the rice plant. Researcher developed different deep learning techniques for crop disease identification, which worked on different dataset of crops. In this paper different rice plant diseases are described. The CNN Inception V3 and SqueezeNet model are used for rice crop disease identification on publically available dataset and comparison of both the module given the paper.