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This study explores the use of a thermal camera and the Faster R-CNN deep learning model for detecting tree trunks in orchards under varying light conditions to assist autonomous robots in navigation. The model demonstrated high accuracy, with a mean Average Precision (mAP) of 0.8529 during validation and 0.8378 during testing, outperforming the YOLO v3 model. The research highlights the potential of thermal imaging in agricultural robotics, particularly in low-light environments, to enhance operational eff

Author

juangomezcafiero

Language

EN