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Plant disease severely affects the crop production. Food security is always a challenge because the population of the world is increasing at a rapid rate. Diseases in plants can be controlled at the initial stage with the help of automatic system that can be able to detect the wide variety of diseases before its spreading to the whole cultivation area. With the development of various machine learning and deep learning algorithms it is now possible to design such an automatic system. Deep neural network like convolution neural network are able to detect the plant disease with high accuracy. In this paper we have discussed about the deep learning techniques, CNN and its parameters, data augmentation, transfer learning and various factor that affects the performance of DL model. Recent studies that apply the machine intelligence in plant leaf disease detection are also discussed.