Machine Learning Based Plant Disease Detection Using EfficientNet B7

Plant diseases have effects on the growth and production of the plant. Plant diseases can be figured out by using digital image processing, and nowadays, Deep learning has made a lot of progress in digital image processing to identify the disease efficiently. This paper finds the plant diseases using EfficientNet by focusing on three data steps: pre-processing, model selection, and detection network, using a canny edge detection algorithm. The model is trained and tested on plant disease data set. The model provides 97.2% accuracy in detecting the disease than existing CNN-based models.