• NIKITHA MARAM
• DR. R. K. SELVAKUMAR
• DR. M. JAIGANESH

Plant disease detection performs a significant role in impressive results in agricultural product yield and quantity. On average smallholder farmers generates more than 80% of agriculture production, for sustainable agriculture production, plant health observation, and disease detection plays an important role. This paper shows the related works on plant disease detection using several algorithms and techniques such as CNN, ANN, SVMs. Here this research proposes a computer vision deep learning model for accurate plant disease detection to overcome the problem. The experimental result shows the 95.2% of model accuracy for the proposed plant disease detection based on the Convolutional neural network. The proposed deep learning model of this research provides a better solution for plant leaf disease detection at an early stage in agriculture production.

Deep learning, convolution neural network, disease detection

"MODIFIED IMAGE BASED PLANT DISEASE DETECTION USING DEEP LEARNING MODEL", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.334-341, June 2019, Available :http://www.jetir.org/papers/JETIR1907P49.pdf

"MODIFIED IMAGE BASED PLANT DISEASE DETECTION USING DEEP LEARNING MODEL", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp334-341, June 2019, Available at : http://www.jetir.org/papers/JETIR1907P49.pdf