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Deep Learning for Coconut Disease Detection by xfeature1111 is a document available to read on EtoBox.

This study presents a hybrid deep learning model, NNSVCLD, for early detection of coconut diseases, achieving high accuracy rates of 98.9% to 99.4% across various folds. The model combines Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) to classify five types of coconut leaf diseases using a dataset of 5036 images. The research highlights the potential of AI in enhancing agricultural practices and improving food security.

Author

xfeature1111

Language

EN