Background: In countries like India, whose primary occupation is agriculture faces a huge loss when the crops get affected by any disease. These diseases attack the crops in various stages and destroy the entire production. Since most of the diseases are transmitted from one crop to another there is much need to detect the exact type of disease the crop has been affected so that farmers can take the required steps to the __ampersandsignldquo;save the crops__ampersandsignrdquo; and production. But detecting the kind of disease that a crop has been affected is very difficult for farmers since there are various kinds of diseases. Method: There are so many classification techniques, such as k-Nearest Neighbor Classifier, Probabilistic Neural Network, Genetic Algorithm, Support Vector Machine, and Main Component Analysis, Artificial Neural Network, and Fuzzy Logic. It is difficult to select the best classification method as compared to other methods the system will be more reliable. This article presents a dissection of various techniques used to find the disease of the plants. Results and Observation: The developed system is capable of detecting diseases in plants and is also capable of providing treatments that can be used against them. To improve the health of the plant, we need to deal with it with sufficient knowledge of the disease and cure. The framework proposed is implemented using python and the google GPU(Graphical Processor Unit) used provided 80 % accuracy. Conclusion: The proposed model used a convolution a neural network model based on SSD mobile network for data training. Some checkpoints are created after training the model. We need to take the last Model Checkpoint to create a file that is used for testing. A particular file type with the.pb extension is created by using the checkpoint file. The model provided 80% of accuracy.