SSL4EO-L: Datasets and Foundation Models for Landsat Imagery
| dc.contributor.author | Stewart, Adam J. | |
| dc.contributor.author | Lehmann, Nils | |
| dc.contributor.author | Corley, Isaac A. | |
| dc.contributor.author | Wang, Yi | |
| dc.contributor.author | Ait Ali Braham, Nassim | |
| dc.contributor.author | Sehgal, Shradha | |
| dc.contributor.author | Robinson, Caleb | |
| dc.contributor.author | Banerjee, Arindam | |
| dc.date.accessioned | 2024-04-16T16:43:52Z | |
| dc.date.available | 2024-04-16T16:43:52Z | |
| dc.date.issued | 2024-04-02 | |
| dc.description.abstract | Landsat: Science, Petabytes, and SSL: [Figure] • Landsat's scientific significance and extended coverage • Petabytes of accessible Landsat imagery • Challenge: diverse sensors, varied wavelengths, and the lack of pre-trained models • Problem: scarcity of large labeled datasets • Solution: self-supervised learning (SSL) | |
| dc.description.department | Electrical and Computer Engineering | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12588/6392 | |
| dc.language.iso | en | |
| dc.publisher | UTSA Graduate School | |
| dc.title | SSL4EO-L: Datasets and Foundation Models for Landsat Imagery | |
| dc.type | Poster |