Kaiming Heis aperson. See:Mask R-CNN. References https://scholar.google.com/citations?user=DhtAFkwAAAAJ 2017 (He et al., 2017) ⇒Kaiming He,Georgia Gkioxari,Piotr Dollár, andRoss Girshick. (2017). “Mask R-cnn.” In: Proceedings of the IEEE International Conference on Computer Vision...
[3] He, Kaiming, et al. "Momentum contrast for unsupervised visual representation learning." Proce...
2023年6月7日 nn.init.kaiming_normal_的简介 nn.init.kaiming_normal_借用了一个叫 Kaiming normal initialization method的方法,见He et al,Delving Deep into Rectifiers: Surpassing Human-Level Performance …
FPNFPN(FeaturePyramidNetworks)是KaimingHe男神和Rgb大神联手的又一力作。主要使用特征金字塔网络来融合多层特征,将底层和高层的特征融合,再利用融合后的特征进行分类和定位。FPN曾在COCO数据集上测试结果排名第一。 原论文地址:FeaturePyramidNetworksfor Object Detection Introduction In ...
同样不会随层数指数衰减或增大,是个可接受的值,跟2.2结论一致。 参考文献 [1] He K, Zhang X, Ren S, et al. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification[C]//Proceedings of the IEEE international conference on computer vision. 2015: 1026-1034. ...
Code of improved1K-layer ResNetswith 4.62% test error on CIFAR-10 in our new arXiv paper:https://github.com/KaimingHe/resnet-1k-layers Citation If you use these models in your research, please cite: These models are converted from our own implementation to a recent version of Caffe (201...
单幅图像去雾翻译(Kaiming_He)).pdf,IEEE 模式分析与机器智能汇刊,33 卷12 刊 2011.12 单幅图像基于暗通道先验的去雾 Kaiming He, Jian Sun, and Xiaoou Tang, Fellow, IEEE 摘要:在本篇论文中,我们提出了一种简单但是有效的图像先验条件——暗通道先验去从一幅输入图 像中
Moco 系列目前已经到了V3版本，之前自己业务上用到了Moco v2，确实在无监督的前提下达到了初版的上线...
He K, Zhang X, Ren S, et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification[C]. international conference on computer vision, 2015: 1026-1034. @article{he2015delving, title={Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet ...
Kaiming He初始化详解 【GiantPandaCV导语】在CNN的训练中,权重初始化是一个比较关键的点。好的权重初始化可以让网络的训练过程更加稳定和高效。本文为大家介绍了kaiming初始化以及详细的推导过程,希望可以让大家更好的理解CNN初始化。 1.为什么需要好的权重初始化...