Chih-Yao MaMin-Hung ChenZsolt KiraGhassan AlRegibSignal Processing: Image CommunicationC.-Y. Ma et al., "TS-LSTM and temporal-inception: exploiting spatio- temporal dynamics for activity recognition," Sig. Proc. Image Comm. 71, 76-87 (2019)....
1)这篇文章做了很多个实验,分析了不同参数的不同的层对识别率到底有什么影响。同时在双流网络的基础上提出了两种融合方式:Temporal Segment LSTM和Temporal-ConvNet。 在双流网络之后有一个Temporal concatenation的过程,即将两种特征concatenated成特征矩阵。 2) Temporal Segment LSTM 提取出特征之后的TS-LSTM最终结构如...
基于Lagrange.Core 实现的 NTQQ 接入框架. Contribute to LSTM-Kirigaya/Lagrange.onebot development by creating an account on GitHub.
基于Lagrange.Core 实现的 NTQQ 接入框架. Contribute to LSTM-Kirigaya/Lagrange.onebot development by creating an account on GitHub.
一个流行的LSTM变种,由Gers & Schmidhuber(2000)提出,增加了“peephole connections”。这意味着我们让gate layer可以看到cell state上面的图中我们向所有的gate layer增加了窥视孔,不过许多论文中只是部分增加。另一个变种是使用耦合 forget and input gates。之前的方式是独立地决定需要忘记哪些信息、增加哪些信息,...
基于Lagrange.Core 实现的 NTQQ 接入框架. Contribute to LSTM-Kirigaya/Lagrange.onebot development by creating an account on GitHub.
基于Lagrange.Core 实现的 NTQQ 接入框架. Contribute to LSTM-Kirigaya/Lagrange.onebot development by creating an account on GitHub.
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Atmosphere 2021, 12(9), 1211; https://doi.org/10.3390/atmos12091211 ActionDateNotesLink article pdf uploaded. 16 September 2021 16:03 CEST Version of Record https://www.mdpi.com/2073-4433/12/9/1211/pdf-vor article xml file uploaded 18 September 2021 07:25 CEST Original file - article ...