| A fully-annotated imagery dataset of sublittoral benthic species in Svalbard, Arctic A Šiaulys, E Vaičiukynas, S Medelytė, S Olenin, A Šaškov, K Buškus, ... Data in brief 35, 106823, 2021 | 12 | 2021 |
| Automated quantification of brittle stars in seabed imagery using computer vision techniques K Buškus, E Vaičiukynas, A Verikas, S Medelytė, A Šiaulys, A Šaškov Sensors 21 (22), 7598, 2021 | 4 | 2021 |
| Application of underwater imagery for the description of upper sublittoral benthic communities in glaciated and ice-free Arctic fjords S Medelytė, A Šiaulys, D Daunys, M Włodarska-Kowalczuk, ... Polar Biology 45 (12), 1655-1671, 2022 | 3 | 2022 |
| Coverage estimation of benthic habitat features by semantic segmentation of underwater imagery from South-eastern Baltic reefs using deep learning models A Šiaulys, E Vaičiukynas, S Medelytė, K Buškus Oceanologia 66 (2), 286-298, 2024 | 2 | 2024 |
| Utilizing sentinel-1 SAR for delineation of narrow intertidal zones and habitat types in Svalbard J Gintauskas, M Bučas, D Vaičiūtė, S Medelytė, E Tiškus, S Olenin International Journal of Remote Sensing 45 (22), 8181-8201, 2024 | | 2024 |
| Dugno bendrijų struktūra besitraukiančio ledyno pakraštyje vakarų Svalbarde, Arktyje S Medelytė Klaipėdos universitetas., 2021 | | 2021 |
| Prototype framework for deep learning driven semantic segmentation of Arctic seabed imagery K Buškus, E Vaičiukynas, A Verikas, S Medelytė, S Olenin Arctic science: Arctic change 2020 conference: book of abstracts 7 (1), 2021 | | 2021 |
| Living on the edge: benthic communities near retreating glaciers S Medelytė, A Šiaulys, S Olenin, K Deja, D Daunys Arctic science: Arctic Change 2020 conference book of abstracts 7 (1), 2021 | | 2021 |
