SINet论文--COD应用场景

In addition to its scientific value, COD is also beneficial for applications in the fields of computer vision (for searchand-rescue work, or rare species discovery),
medical image segmentation (e.g., polyp segmentation [14], lung infection segmentation [18, 67]),
agriculture (e.g., locust detection to prevent invasion),
and art (e.g., for photo-realistic blending [21], or recreational art [6]).

除了它的科学价值，COD也有利于计算机视觉领域的应用
(搜索和救援工作，或稀有物种的发现)，

医学图像分割(如息肉分割[14]、肺部感染分割[18,67]);

农业(例如，侦测蝗虫以防止入侵);

艺术(例如，用于逼真的混合[21]，或娱乐艺术[6])。

医学 \cite{2022-MICCAI-LDNet} [14 18 67]
农业
艺术 [21, 6]
生态和城市检测

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[14] Deng-Ping Fan, Ge-Peng Ji, Tao Zhou, Geng Chen, Huazhu Fu, Jianbing Shen, and Ling Shao.
PraNet: Parallel Reverse Attention Network for Polyp Segmentation.