• Dr J.Savitha
• Kanimozhi N
• Sansia Begum M
• Keerthana Priya S

Agriculture plays a major role in human life. Almost 60% of the population is involved directly or indirectly in some agriculture activity. In the classical system no more technologies to detect the diseases regarding various crop in an agricultural environment, that’s why farmers are not interesting to increase their agricultural productivity day by day. Crop diseases affect the growth of their respective species; therefore their early identification is very important. Many Machine Learning (ML) models have been employed for the detection and classification of crop diseases but, after the advancements in a subset of ML, that is, Deep Learning (DL), this area of research appears to have great potential in terms of increased accuracy. Here in the proposed system convolution neural network and Deep Neural Network can be efficiently and accurately detect and classify the symptoms of crop diseases. Moreover, several performance metrics are used for the evaluation of these techniques. This review provides a comprehensive explanation of DL models used to visualize crop diseases. In addition, some research gaps are identified from which to obtain greater transparency for detecting diseases in plants, even before their symptoms appear clearly. This proposed methodology aims to create an approach for plant leaf disease detection based on convolution neural network.

Deep Learning, Diseases ,Agriculture, identification, plant .

"PLANT DISEASE DEDUCTION USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.d393-d397, July-2023, Available :http://www.jetir.org/papers/JETIR2307350.pdf

"PLANT DISEASE DEDUCTION USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppd393-d397, July-2023, Available at : http://www.jetir.org/papers/JETIR2307350.pdf