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A project to train and evaluate different dnn models for plant disease detection problem, tackle the problem of scarce real-life representative data, experiment with different generative networks and generate more plant leaf image data and implement segmentation pipeline to avoid miss-classification due to unwanted input
Plant disease detection using VGG16 model, which is a pre-trained model that has been trained on a large dataset of images.
Identify leaves from flavia dataset using scikit learn and python