RiceLeaf-disease-detection and Rice-Disease-Classfication
These tools are competitors, as both are Deep Learning projects using Transfer Learning (EfficientNet and Hybrid deep CNN, respectively) for the classification and identification of various rice leaf diseases.
About RiceLeaf-disease-detection
vinodbavage31/RiceLeaf-disease-detection
A Deep Learning project using Transfer Learning (EfficientNet) and Data Augmentation to classify three major rice leaf diseases (Bacterial Blight, Brown Spot, Leaf Smut). Provides a robust, high-accuracy model for early disease detection in precision agriculture.
About Rice-Disease-Classfication
MHassaanButt/Rice-Disease-Classfication
In this project, I used Hybrid deep CNN transfer learning on rice plant images, perform classification and identification of various rice diseases. I employed Transfer Learning to generate our deep learning model using Rice Leaf Dataset from a secondary source. The proposed model is 90.8% accurate, Experiments show that the proposed approach is viable, and it can be used to detect plant diseases efficiently.
This tool helps rice farmers, agricultural scientists, and crop inspectors quickly identify common rice plant diseases. By analyzing images of rice plants, it can classify various diseases, helping you understand what's affecting your crops. The output is a clear identification of the specific disease present, allowing for timely intervention.
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