This is the first general Underwater Image Instance Segmentation (UIIS) dataset containing 4,628 images for 7 categories with pixel-level annotations for underwater instance segmentation task
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Extension of the PASTIS benchmark with radar and optical image time series.
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…While deep learning techniques are widely used in medical image segmentation and have been applied to the ICH segmentation task, existing public ICH datasets do not support the multi-class segmentation To address this, we develop the Brain Hemorrhage Segmentation Dataset (BHSD), which provides a 3D multi-class ICH dataset containing 192 volumes with pixel-level annotations and 2200 volumes with slice-level To demonstrate the utility of the dataset, we formulate a series of supervised and semi-supervised ICH segmentation tasks.
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…The dataset is designed to do binary semantic segmentation of burned vs unburned areas.
From my knowledge, the dataset used in the project is the largest crack segmentation dataset so far. It contains around 11.200 images that are merged from 12 available crack segmentation datasets. Qingquan and Mao, Qingzhou and Wang, Song}, journal={Pattern Recognition Letters}, volume={33}, number={3}, pages={227--238}, year={2012}, publisher={Elsevier} } https://github.com/alexdonchuk/cracks_segmentation_dataset https://github.com/yhlleo/DeepCrack https://github.com/ccny-ros-pkg/concreteIn_inpection_VGGF (Citing from https://github.com/khanhha/crack_segmentation.)
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