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语义分割

语义分割将类别标签分配给图像中的每个像素，生成密集、经过类别注释的场景图。与绘制边界框的目标检测不同，它勾勒出每个类别的精确空间范围，这在医学成像、自动驾驶、卫星分析以及任何需要精确区域边界的任务中都不可或缺。

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语义分割
微调语义分割图像分类实例分割目标检测基于卷积神经网络的迁移学习领域自适应实例分割领域自适应视觉 Transformer可解释图像分类可解释实例分割可解释目标检测

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来源

  1. Long, J., Shelhamer, E., & Darrell, T. (2015). Fully convolutional networks for semantic segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3431–3440. DOI: 10.1109/CVPR.2015.7298965 ↗
  2. Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2018). DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(4), 834–848. DOI: 10.1109/TPAMI.2017.2699184 ↗

如何引用本页

ScholarGate. (2026, June 3). Semantic Segmentation (Dense Pixel-wise Classification). ScholarGate. https://scholargate.app/zh/deep-learning/semantic-segmentation

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被引用于

领域自适应实例分割领域自适应视觉 Transformer可解释图像分类可解释实例分割可解释目标检测可解释的语义分割可解释视觉 Transformer微调语义分割微调视觉Transformer图像分类实例分割多语言语义分割多模态实例分割多模态目标检测多模态语义分割目标检测自监督实例分割自监督语义分割半监督实例分割半监督语义分割基于卷积神经网络的迁移学习实例分割迁移学习弱监督卷积神经网络弱监督实例分割弱监督语义分割

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ScholarGate — Semantic Segmentation (Semantic Segmentation (Dense Pixel-wise Classification)). 于 2026-06-15 检索自 https://scholargate.app/zh/deep-learning/semantic-segmentation · 数据集： https://doi.org/10.5281/zenodo.20539026