Machine learningDeep learning / NLP / CV
图像分类
图像分类是指从一组固定的类别中为整个图像分配单个语义标签的任务。现代方法依赖于深度卷积神经网络（CNN）或视觉 Transformer（ViT），在 ImageNet 等大型标记数据集上进行端到端训练，在许多基准测试中达到超乎人类的准确率，并支撑着从医学成像到自动驾驶汽车等应用。
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Method map
The neighbourhood of related methods — select a node to explore.
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来源
- Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). ImageNet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems (NeurIPS), 25, 1097–1105. link ↗
- He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 770–778. DOI: 10.1109/CVPR.2016.90 ↗
如何引用本页
ScholarGate. (2026, June 3). Deep Learning Image Classification. ScholarGate. https://scholargate.app/zh/deep-learning/image-classification
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 微调图像分类深度学习↔ compare
- 目标检测深度学习↔ compare
- 语义分割深度学习↔ compare
- 迁移学习在图像分类中的应用深度学习↔ compare
- Vision Transformer深度学习↔ compare