Crop Disease Detection using Deep Learning employs the ResNet29 model to identify and diagnose 38 distinct crop diseases. Utilizing the Plant Village dataset, this project achieves high accuracy in detecting diseases, helping to improve agricultural sustainability through timely and automated disease detection.
deep-learning agriculture tensorflow pytorch neural-networks image-classification crop-disease-detection ai-for-agriculture resnet29 plant-village-dataset
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Updated
Nov 17, 2024 - Jupyter Notebook