Plant Disease Detection and Comparison Using DL, ML Techniques
Keywords:
Convolutional Neural Network, Deep Learning, Hygiene CropsAbstract
Crop diseases and pesticides are essential determinants of plant production and quality. Digital image analysis can be used to identify crop diseases and suggest pests. Deep learning is much superior to conventional approaches in recent years of advances in the area of digital image processing. How to study crop diseases and pesticides through deep learning technologies has become a major research topic for researchers. We compare three plants in this project 1) Salvation; 2) Sabdarifa Hibiscus 3) Oleracea brassica for disease detection and pesticide suggestion.This study defines the issue of identification of crop diseases, compares it with conventional plant diseases and methods of detection of pests. This report outlines studies on plant diseases focused on in-depth learning in the last years, based on the disparity in the network structure. In this project we use the CNN model to diagnose diseases of the plants and the disease-related pesticide.
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