Detection of Green Leaf Disease by Image Processing using CNN
Authors/Creators
- 1. Assistant Professor, Department of Electronics and Instrumentation Engineering, Dr. Ambedkar Institute of Technology, Near Jnana Bharathi Campus, Mallathahalli, Bengaluru, Karnataka, India
- 2. Student, Department of Electronics and Instrumentation Engineering, Dr. Ambedkar Institute of Technology, Near Jnana Bharathi Campus, Mallathahalli, Bengaluru, Karnataka, India
Description
The convolutional neural networks (CNNs) approach for image classification has a scope to identify the different plant leaf disease. It is possible to implement a innovative way of training the algorithm and methodology enable a good performing and easy system design for practical application. The developed model can recognize three types of leaf diseases and pesticides and/or fertilizers are advised according to the severity of the diseases. The type of green leaf diseases is recognized by CNN. After recognition, the predictive remedies are suggested that can help agriculture related people and organizations to take appropriate actions against these diseases. The image analysis is done by using k-means clustering algorithm which help to group and differentiate the plant leaves based on disease.
Files
Detection of Green Leaf Disease by Image Processing using CNN.pdf
Additional details
References
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