• Bhavesh Lohana
• Nikhil Gangaramani
• Tanish Sahijwani
• Aakash Chauhan
• Vidya Zope

In the plant production industry plant growth monitoring and plant protection are some of the most important elements. The productivity and quality of plants are influenced by these factors. One of the major factors that deteriorate plant health is diseases. The use of computer vision techniques, machine learning algorithms, and deep learning models have gained value due to their capability of dealing with complex data with accuracy. These techniques are very widely used for pattern recognition and classification problems. Therefore in this work, a multilayer convolutional neural network is proposed for the classification of the plant species and diseased plant leaf images. The main objective of our project is to build an online application that identifies the plant species from leaf image and gives a description of that plant. And it detects that the plant has any disease, simultaneously.

Computational Neural Network, Deep Learning, Machine Learning, Image Processing, Plant Classification, Disease Detection.

"A Deep Learning Approach to Classify Plant and Detect Disease ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.251-258, October-2021, Available :http://www.jetir.org/papers/JETIRFD06038.pdf

"A Deep Learning Approach to Classify Plant and Detect Disease ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. pp251-258, October-2021, Available at : http://www.jetir.org/papers/JETIRFD06038.pdf