Intrarow Uncut Weed Detection Using You-Only-Look-Once Instance Segmentation for Orchard Plantations
Intrarow Uncut Weed Detection Using You-Only-Look-Once Instance Segmentation for Orchard Plantations is a scholarly work, published in 2024 in ''Sensors''. The main subjects of the publication include instance segmentation, segmentation, precision agriculture, artificial intelligence, grafting, computer vision, simulation, Phoenix dactylifera, orchard, tree, GNSS applications, and computer science. Therefore, the objective of this study is to develop a vision module using a custom-trained dataset on YOLO instance segmentation algorithms to support autonomous robotic weeders in recognizing uncut weeds and obstacles (i.e., fruit tree trunks, fixed poles) within rows.