Classification of plantations from RPA images using deep learning

In this study, we explored the application of Deep Learning techniques for the classification of coconut plantations from images collected by a Remotely Piloted Aircraft (RPA). A Convolutional Neural Network was used to create a model that classifies images into two categories: coconut and non-coconut. The model achieved an accuracy of 88%, concluding that Deep Learning techniques are viable tools for the identification of plants in large areas, with the potential to improve the management of agricultural crops.