Abstract
In many countries, agriculture has an excess impact on life of human beings and economic status. As leaf plays an important role, it gives information about the quantity and quality of agriculture yield depending upon the condition in advance. In this paper, we proposed the system which focuses on the detection of disease in plant leaves using Deep Learning approach. The main two processes that we used in our system are GUL Application and Deep Learning. We used CNN for classification of diseases and Remedy Recommendation upon diseased leaf selected from the Plant Village Dataset. This dataset consists of both healthy and unhealthy leaves. Our results show that the CNN Model achieves 96% accuracy for 8 epochs using Tensor flow
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Online and Biomedical Engineering (iJOE)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
