Machine learning
DenseNet
DenseNet（密集连接卷积网络）由 Huang、Liu、van der Maaten 和 Weinberger 于 2017 年在 CVPR 上提出（最佳论文奖），它将一个密集块内的每一层与该块内的所有后续层连接起来，使得每一层接收所有先前层连接起来的特征图——最大化特征重用，增强梯度流，并以显著更少的参数实现与类似架构（如 ResNet）相比具有竞争力的准确率。
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来源
- Huang, G., Liu, Z., van der Maaten, L., & Weinberger, K. Q. (2017). Densely Connected Convolutional Networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 4700–4708. DOI: 10.1109/CVPR.2017.243 ↗
- Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. ISBN: 978-0-262-03561-3 ↗
如何引用本页
ScholarGate. (2026, June 3). Densely Connected Convolutional Network (DenseNet). ScholarGate. https://scholargate.app/zh/deep-learning/densenet
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