31 citations · 65 across the 5 of their papers we have counts for
5 papers
PLAS-Net: Pixel-Level Area Segmentation for UAV-Based Beach Litter Monitoring
Yongying Liu, Jiaqi Wang, Jian Song +6
Accurate quantification of the physical exposure area of beach litter, rather than simple item counts, is essential for credible ecological risk assessment of marine debris. Howeve…
Multi-label classification for multi-temporal, multi-spatial coral reef condition monitoring using vision foundation model with adapter learning
Xinlei Shao, Hongruixuan Chen, Fan Zhao +5
Coral reef ecosystems provide essential ecosystem services, but face significant threats from climate change and human activities. Although advances in deep learning have enabled a…
BRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster response
Hongruixuan Chen, Jian Song, Olivier Dietrich +9
Disaster events occur around the world and cause significant damage to human life and property. Earth observation (EO) data enables rapid and comprehensive building damage assessme…
Riverbed litter monitoring using consumer-grade aerial-aquatic speedy scanner (AASS) and deep learning based super-resolution reconstruction and detection network
Fan Zhao, Yongying Liu, Jiaqi Wang +5
Underwater litter is widely spread across aquatic environments such as lakes, rivers, and oceans, significantly impacting natural ecosystems. Current monitoring technologies for de…
Deep learning for multi-label classification of coral conditions in the Indo-Pacific via underwater photogrammetry
Xinlei Shao, Hongruixuan Chen, Kirsty Magson +4
Since coral reef ecosystems face threats from human activities and climate change, coral conservation programs are implemented worldwide. Monitoring coral health provides reference…