1.意图识别是利用encoder中的最后一个time step中的双向隐层,再加上平均池化或者利用attention加权平均,最后接一个fc层进行分类 2.槽填充是序列标注,双向隐状态加attention权重,再经过一个单元grucell,最后接一个fc层分类。这里注意一点是,槽的每一步的预测输出会输入到grucell中的前向传输时间步中。 3.总的loss...
在Encoder-Decoder框架中，文本经过编码器形成表征后，分别通过两个解码器得到意图与槽。解码器分为三种类型，依据是否将编码器对应位置的隐层状态输入到解码器的每个步骤标注槽。Attention-Based RNN框架则不同，此框架仅包含RNN，没有解码器部分，解码过程与RNN融为一体。总结：本文成文于2016年，结构清晰...
Inspired by the coarse-to-fine hierarchical process, we propose an end-to-end RNN-based Hierarchical Attention (RNN-HA) classification model for vehicle re-identification. RNN-HA consists of three mutually coupled modules: the first module generates image representations for vehicle images, the ...
Inspired by the coarse-to-fine hierarchical process, we propose an end-to-end RNN-based Hierarchical Attention (RNN-HA) classification model for vehicle re-identification. RNN-HA consists of three mutually coupled modules: the first module generates image representations for vehicle images, the ...
To address these problems, we propose an Attention-based Bidirectional CNN-RNN Deep Model (ABCDM). By utilizing two independent bidirectional LSTM and GRU layers, ABCDM will extract both past and future contexts by considering temporal information flow in both directions. Also, the attention ...
Feint attack, as a combination of virtual attacks and real attacks of a new type of APT attack, has become the focus of attention. Under the cover of virtual attacks, real attacks can achieve the real purpose and...
2.4. CAPTCHA Recognition with Attention Mechanisms and Transformers Attention mechanisms allow networks to give more attention to certain channels and regions of a CAPTCHA. The Convolutional Block Attention Module (CBAM), conceived by Woo et al., is set to be integrated into any classification network...
In Figure 7, we can further observe that 𝑀=8M=8 is a point that requires our utmost attention. If the number of parallel frames exceeds 8, the MEMAP value will rise sharply. After a lot of trials, one fact that was proven is that our decoder was no longer capable of decoding prop...
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction. Yao Qin, Dongjin Song, Haifeng Cheng, Wei Cheng, Guofei Jiang, Garrison. W. Cottrell International Joint Conference on Artificial Intelligence (IJCAI), 2017. run in tf 1.3 This repository is used to obtain a basel...
The pair-wise attention mechanism is used to understand the relationship between the modalities and their importance before fusion. First, two-two combinations of modalities are fused at a time and finally, all the modalities are fused to form the trimodal representation feature vector. The ...