Automated underwater image analysis reveals sediment patterns and megafauna distribution in the tropical Atlantic
Abstract The deep-sea comprises diverse habitats and species whose characterisation provides crucial insights into the health and resilience of our oceans. Whereas direct sampling enables investigation of the vertical variability of the seafloor at small spatial scales, optical imaging allows for mu...
Saved in:
| Main Authors: | Benson Mbani, Jens Greinert |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-12723-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multi-AUV sediment plume estimation using Bayesian optimization
by: Tim Benedikt von See, et al.
Published: (2025-01-01) -
Feces, fungus, and the fall of megafauna
by: Paul L. Koch
Published: (2010-04-01) -
Automated recognition of deep-sea benthic megafauna in polymetallic nodule mining areas based on deep learning
by: Guofan Long, et al.
Published: (2025-12-01) -
Role of megafauna and frozen soil in the atmospheric CH4 dynamics.
by: Sergey Zimov, et al.
Published: (2014-01-01) -
Collagen peptide markers for three extinct Australian megafauna species
by: Carli Peters, et al.
Published: (2025-06-01)