Publication

Abstract : Many nations depend heavily on the production of coconut trees, and early detection of pests can help preserve crop yields. It takes a lot of time and effort to find pests in coconut trees using traditional methods. The detection procedure can be automated to increase its accuracy and efficiency using deep learning techniques like CNN, ANN(Artificial Neural Networks) or a hybrid between them such as CNN and Autoencoders. Photos of coconut trees taken on a drone and cameras mounted on a monopod to spot pests, to increase efficacy and accuracy, the deep learning system is trained using a dataset of pictures of coconut trees with and without pests based on the classification of images of coconut leaves. The features we looked for were biological defects caused by living agents The method can be used to keep track of the conditions of coconut trees over time, which could increase agricultural output.