Aerial Identification of Amazonian Palms in High-Density Forest Using Deep Learning

This paper presents an integrated aerial system for the identification of Amazonian Moriche palm (Mauritia flexuosa) in dense forests, by analyzing UAV-captured RGB imagery using a Mask R-CNN deep learning approach. The model was trained with 478 labeled palms, transfer technique based on well-known MS COCO framework©. Comprehensive in-field experiments were conducted yielding precision 98%. proposed is fully automatic and suitable inventory this species above 60 m, under complex climate soil conditions.