PLAS-Net performs instance segmentation on UAV beach images to extract precise physical areas of litter objects, reporting 58.7% mAP_50 and enabling new ecological analyses such as area-weighted risk mapping and an abundance-area paradox in litter sources.
Assessment of marine debris on hard-to-reach places using unmanned aerial vehicles and segmentation models based on a deep learning approach.Sustainability, 14(14), 2022
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PLAS-Net: Pixel-Level Area Segmentation for UAV-Based Beach Litter Monitoring
PLAS-Net performs instance segmentation on UAV beach images to extract precise physical areas of litter objects, reporting 58.7% mAP_50 and enabling new ecological analyses such as area-weighted risk mapping and an abundance-area paradox in litter sources.