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"LEAF BASED PLANT DISEASE DETECTION USING DEEPLEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 1, page no.47-51, January-2021, Available :http://www.jetir.org/papers/JETIR2101005.pdf

• G PRATHYUSHA
• Dr. D. Vivekananda Reddy

Agriculture is an important sector in any country, particular in India the agriculture is the major occupation. In the agriculture sector the major problem is plants affecting with the disease. When plants are infected with the disease, there will not be good yield, the fruits,grains,vegetables from the plants also will not be in a healthy conditions. So the demands for that particular plant products will decrease. Then the farmers expected profits will not be reached, instead they face the lot of losses. So the identifying the plant disease at right time before it spreads and affect the complete crops. Then after identifying the plant disease, the proper diagnosis should be taken to identify what is the disease the plant is effected and proper measures has to be taken to decrease the disease and control it. In this disease detection is the major task, then measures to be taken for the particular disease. The some of the previous approaches for this problem are identifying the plant disease with the nacked eye, using image processing techniques, using machine learning techniques. The previous work are proposed to identify the only few plant diseases. In this paper the identifying of the 38 classes of the diseases are proposed. These classes contain the various diseases of various plants. The proposed method used to identify these 38 Classes of diseases by using deep learning. The 38 classes contain both the diseased plants and healthy plant. In this the user interface is developed using the Django framework, by this the user can interact with the proposed system easily.

Deep learning, Digital Image, Plant diagnosis, Django, Convolutional Neural Network (CNN)

"LEAF BASED PLANT DISEASE DETECTION USING DEEPLEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 1, page no. pp47-51, January-2021, Available at : http://www.jetir.org/papers/JETIR2101005.pdf