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- 13952176 type Dataset assertion.
- 13952176 type Resource assertion.
- 13952176 type MediaObject assertion.
- 13952176 description "Three underwater macro-litter image datasets for object detection in YOLO format: UNO dataset: All details are available in From TrashCan to UNO: Deriving an Underwater Image Dataset to Get a More Consistent and Balanced Version, C.Barrelet et al, ICPR 2022 MORGANE dataset: Images taken in shallow water in the harbors near Montpellier, France VENICE dataset: Images taken during the MAELSTROM experiments in Venice, Italy" assertion.
- 13952176 dateCreated "2025-06-11 10:55:01.395983+00:00" assertion.
- 13952176 name "Underwater macro-litter image datasets" assertion.
- 13952176 contentUrl "https://zenodo.org/records/13952176" assertion.
- 13952176 creator mailto:taha.lahami@ve.ismar.cnr.it assertion.
- 13952176 dateModified "2025-10-14 08:34:02.912218+00:00" assertion.
- 13952176 license legalcode assertion.
- 13952176 sdDatePublished "2025-06-11 10:55:01.395983+00:00" assertion.
- 13952176 author mailto:taha.lahami@ve.ismar.cnr.it assertion.