A Comprehensive Review on Plant Disease Diagnosis and Controlling using Convolutional Neural Networks

Rice plant diseases cause to reduce 37% of Rice productions annually. This happens due to late detection of diseases and lack of knowledge about Rice plant diseases. This could be overcome by developing a software application for farmers which is capable of identifying plant diseases through it and give solutions for those diseases. For this disease identification process, Convolutional Neural Networks can directly be used as it is very efficient in image identification and classification. Even though this approach has followed by many researchers for plant disease detection, comparatively low researches are conducted on identifying rice plant diseases. This paper gives a clear idea about existing rice plant diseases and how Deep Learning methodologies are used for identifying those diseases, also it reviews different type of technologies which were used in the literature by comparing each of them with their advantages and disadvantages, as the final conclusion of this review author could able to identify the most efficient methods in each steps of image detection process which will be important for identify rice plant diseases.