A novel Approach for Palm Tree Leaf Disease Classification using Convolutional Neural Networks - E.Aravind , M.Soujanya (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Palm trees hold significant ecological and economic value but are often vulnerable to diseases threatening their well-being. Timely detection of these diseases is crucial for managing and safeguarding crop productivity. In this study, we propose a novel hybrid approach integrating Convolutional Neural Networks (CNNs) for feature extraction and Random Forests for classification, aiming to discern between normal and spotted palm tree leaves. Our methodology exhibits outstanding performance, achieving an accuracy of 0.84, surpassing standalone methods. Our approach demonstrates resilience to environmental variations and complexities associated with palm tree diseases. These findings highlight the transformative potential of deep learning and ensemble learning techniques in advancing palm tree disease detection and management strategies.