• Faizan Shaikh
• Hritik Bhawale
• Atharva Avade
• Varun Jadhav
• Rubeena Khan

Grapes are basically a tropical plant with excellent pulp, rich color and very beneficial health. In general, it is timeconsuming and difficult for farmers in remote areas to diagnose grapevine diseases due to the unavailability of specialists. Although experts are located in some areas, diagnostic tests are performed with the naked eye resulting in misdiagnosis. The default system can alleviate these problems. The disease on the grape plant usually starts on the leaf and then spreads to the stem, root and fruit. When the disease reaches the fruit the whole plant is destroyed. The procedure is to detect the disease in the leaf itself to save the fruit. In our proposed system we have used the Convolutional Neural Network. The leaf image is taken using the built-in mobile camera module. The achieved accuracy is 98.23% in powdery mildew against bacterial spots.

Deep learning, Convolutional Neural Network, Grapes leaf Disease

"Grape Leaf Disease Detection Using Image Processing & Cnn", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 3, page no.f393-f396, March-2022, Available :http://www.jetir.org/papers/JETIR2203551.pdf

"Grape Leaf Disease Detection Using Image Processing & Cnn", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 3, page no. ppf393-f396, March-2022, Available at : http://www.jetir.org/papers/JETIR2203551.pdf