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@article{156213,
        author = {Samir Dilawar Sande and Sanket Satish Patil and Gaurav Rajendra Salunkhe and I. Y. Inamdar},
        title = {Diagnosis And Identification of Plant Disease},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {3},
        pages = {41-44},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=156213},
        abstract = {Agriculture is one of the most important source in subsistence. The village peoples depends on the agriculture in India. Agriculture consists of different plants and 70% to 72% peoples are dependent on it. If the plant or crops are infected by disease, it will directly influence the economy and production of agriculture. The leaves are most important part for fast growing of plants. Identification of plants leaves disease is a challenge to farmers.  This paper focuses on the last decade traditional methods , Machine learning methods (e.g KNN, ANN, Supervise Learning,  Unsupervised Learning ,Reinforcement Learning )and Deep Learning Method (e.g CNN).After reviewing on existing methods we observed that deep learning method is the best for plant disease detection.},
        keywords = {CNN, Graphical User Interface, Image Processing, Deep learning, ANN.},
        month = {},
        }