Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/124484
| Title: | LOTS: Litter on the Sand dataset for litter segmentation | Authors: | Barra, Paola Citarella, Alessia Auriemma Orefice, Giosue Castrillon-Santana, Modesto Ciaramella, Angelo |
UNESCO Clasification: | 33 Ciencias tecnológicas | Keywords: | Photography Image segmentation Image resolution Ecosystems Virtual environments, et al |
Issue Date: | 2023 | Journal: | IEEE Access | Conference: | 18th International Conference on Machine Vision Application (MVA 2023) | Abstract: | The marine ecosystem is threatened by human waste released into the sea. One of the most challenging marine litter to identify and remove are the small particles settled on the sand which may be ingested by local fauna or cause damage to the marine ecosystem. Those particles are not easy to identify because they get confused with maritime/natural material, natural elements such as shells, stones or others, which can not be classified as "litter". In this work we present a dataset of Litter On The Sand (LOTS), with images of clean, dirty and wavy sand from 3 different beaches. | URI: | http://hdl.handle.net/10553/124484 | DOI: | 10.23919/MVA57639.2023.10216220 | Source: | Proceedings of MVA 2023 - 18th International Conference on Machine Vision Applications (MVA) Hamamatsu, Japan, July 23-25, 2023 |
| Appears in Collections: | Actas de congresos |
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