International Journal of Science, Engineering and TechnologyAuthors: Associate Prof Chandani Lachake, Shreyas Gogawale, Mahesh Sakhare
Abstract: This study proposes an automated system for the early identification of banana plant diseases using Deep Learning and Transfer Learning techniques. By leveraging pre-trained convolutional neural network (CNN) architectures—such as ResNet or MobileNet—the model effectively classifies common pathologies like Black Sigatoka, Panama Wilt, and Banana Bunchy Top Virus from leaf imagery. Transfer learning is utilized to overcome the limitations of small datasets, ensuring high feature extraction accuracy while significantly reducing training time. The integrated approach achieves superior classification performance compared to traditional manual inspection, providing a scalable solution for small-scale farmers.
