resnet18参考文献
时间: 2023-10-11 13:14:27 浏览: 262
ResNet18是由Kaiming He等人于2016年提出的一种深度残差网络,用于解决深度神经网络中的退化问题。该网络结构通过引入残差连接(residual connections)来解决梯度消失和梯度爆炸的问题,从而能够训练更深的网络。
以下是关于ResNet18的参考文献:
1. He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 770-778).
2. He, K., Zhang, X., Ren, S., & Sun, J. (2016). Identity mappings in deep residual networks. In European conference on computer vision (ECCV) (pp. 630-645).
3. Kaiming He's homepage: https://www.cs.cmu.edu/~kaiminghe/
相关问题
resnet的参考文献
He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 770-778).
He, K., Zhang, X., Ren, S., & Sun, J. (2016). Identity mappings in deep residual networks. In European conference on computer vision (pp. 630-645).
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. (2015). Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification. In Proceedings of the IEEE International Conference on Computer Vision (ICCV) (pp. 1026-1034).
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. (2015). Convolutional Neural Networks with Low-rank Regularization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 5967-5975).
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. (2015). Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 346-361).
ResNet-50 文献引用
如果您需要引用ResNet-50的文献,请使用以下参考文献格式:
He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 770-778).
这是原始的ResNet-50论文,它详细介绍了ResNet架构和深度残差学习的概念。请确保在引用时遵循适当的引用格式和规范。