Plant Disease Detection Using Transfer
Keywords:
Plant Disease Detection, ResNet50, Machine learning, Deep Neural Network, Transfer LearningAbstract
Agriculture plays a crucial role in human lives, with around 70% of the population directly or indirectly involved in it. However, traditional approaches lack tools to identify diseases in crops and increase agricultural output. Early detection of crop diseases is vital as they impact plant growth and pose a significant threat to food security. Machine Learning (ML) models have been used to identify and categorize agricultural diseases, but recent advancements in Deep Learning show promise for improved accuracy. This proposed method utilizes convolutional neural networks and deep neural networks to effectively and accurately identify and recognize crop disease symptoms. By training deep learning models using large publicly available datasets, it becomes possible to detect plant diseases on a large scale.
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