Datasets > Modality > Images > SUIM (Segmentation of Underwater IMagery)

SUIM (Segmentation of Underwater IMagery)

Introduced by Islam et al. in Semantic Segmentation of Underwater Imagery: Dataset and Benchmark

The Segmentation of Underwater IMagery (SUIM) dataset contains over 1500 images with pixel annotations for eight object categories: fish (vertebrates), reefs (invertebrates), aquatic plants, wrecks/ruins, human divers, robots, and sea-floor. The images have been rigorously collected during oceanic explorations and human-robot collaborative experiments, and annotated by human participants.

Source: Semantic Segmentation of Underwater Imagery: Dataset and Benchmark

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