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The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment

机译:用于海洋水产养殖环境中的入侵物种语义分割的Ciona17数据集

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An original dataset for semantic segmentation, Ciona17, is introduced, which to the best of the authors' knowledge, is the first dataset of its kind with pixel-level annotations pertaining to invasive species in a marine environment. Diverse outdoor illumination, a range of object shapes, colour, and severe occlusion provide a significant real world challenge for the computer vision community. An accompanying ground-truthing tool for superpixel labeling, Truth and Crop, is also introduced. Finally, we provide a baseline using a variant of Fully Convolutional Networks, and report results in terms of the standard mean intersection over union (mIoU) metric.
机译:引入了用于语义分割的原始数据集Ciona17,据作者所知,该数据集是同类中的第一个数据集,其像素级注释与海洋环境中的入侵物种有关。多样的室外照明,各种物体形状,颜色和严重的遮挡为计算机视觉界带来了巨大的现实挑战。还介绍了用于超像素标记的配套地面校正工具“真相和裁剪”。最后,我们使用完全卷积网络的变体提供基线,并以标准平均相交联合(mIoU)度量报告结果。

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