2026-10-14T13:03:18Z https://data.mendeley.com/oai

oai:data.mendeley.com/sgx3mnxj5h.1 2024-12-17T18:47:28Z

Kim, Solhee YOLO-Seg Model with Tiling Movement for Detecting Paddy Parcels using High-Resolution Drone Image Mendeley Data This study aims to develop a system that combines object detection and segmentation capabilities in high-resolution images using the YOLO-Seg model for paddy parcel monitoring based on drone imagery. For the first time, we propose a novel tiling movement technique and systematically analyze optimal overlap rates to reduce tile boundary errors that occur in large-scale drone image processing. Boundary Delimitation Machine Learning Algorithm Jeon, Jeongbae Kim, Taegon Dataset doi:10.17632/sgx3mnxj5h.1 oai:data.mendeley.com/sgx3mnxj5h.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/sgx3mnxj5h 2024-12-17T18:47:28Z