TOWARDS DETECTING FLOATING OBJECTS ON A GLOBAL SCALE WITH LEARNED SPATIAL FEATURES USING SENTINEL 2

16 citations as recorded by crossref.

1. Experimental observations of marginally detectable floating plastic targets in Sentinel-2 and Planet Super Dove imagery D. Papageorgiou & K. Topouzelis 10.1016/j.jag.2024.104245
2. Taking Artificial Intelligence Into Space Through Objective Selection of Hyperspectral Earth Observation Applications: To bring the “brain” close to the “eyes” of satellite missions A. Wijata et al. 10.1109/MGRS.2023.3269979
3. Detecting Marine pollutants and Sea Surface features with Deep learning in Sentinel-2 imagery K. Kikaki et al. 10.1016/j.isprsjprs.2024.02.017
4. Meta-learning to address diverse Earth observation problems across resolutions M. Rußwurm et al. 10.1038/s43247-023-01146-0
5. Detection of floating marine macro plastics using a new index with remote sensing data K. Pathira Arachchilage et al. 10.1007/s00343-024-3152-7
6. Sentinel-2 Detection of Floating Marine Litter Targets with Partial Spectral Unmixing and Spectral Comparison with Other Floating Materials (Plastic Litter Project 2021) D. Papageorgiou et al. 10.3390/rs14235997
7. The fishnet-harvesting buoy to collect ghost nets in the ocean: Technology concept and feasibility T. Defraeye & K. Shoji 10.1016/j.apor.2024.104062
8. Riverine litter monitoring from multispectral fine pixel satellite images S. Garaba & Y. Park 10.1016/j.envadv.2023.100451
9. Detection and Monitoring of Floating Plastic Debris on Inland Waters From Sentinel-2 Time Series D. Cerra et al. 10.1109/JSTARS.2024.3502796
10. Machine learning-based detection and mapping of riverine litter utilizing Sentinel-2 imagery A. Mohsen et al. 10.1007/s11356-023-27068-0
11. Deep learning for detecting macroplastic litter in water bodies: A review T. Jia et al. 10.1016/j.watres.2023.119632
12. Optical Detection of Marine Debris Using Deep Knockoff M. Olyaei et al. 10.1109/TGRS.2022.3228638
13. Assessing the Effect of Water on Submerged and Floating Plastic Detection Using Remote Sensing and K-Means Clustering L. Fronkova et al. 10.3390/rs16234405
14. On advances, challenges and potentials of remote sensing image analysis in marine debris and suspected plastics monitoring O. Karakuş 10.3389/frsen.2023.1302384
15. Ground Resolved Distance Estimation of Sentinel-2 Imagery Using Edge-based Scene-Driven Approach F. Dadrass Javan et al. 10.1007/s41064-024-00330-x
16. Monitoring Waste From Uncrewed Aerial Vehicles and Satellite Imagery Using Deep Learning Techniques: A Review B. Wang et al. 10.1109/JSTARS.2024.3488056