Then, an ODAM (optimized dual-attention mechanism) module is constructed to further improve the integration effect. Moreover, a MO module is used to improve the network's feature extraction capability for contextual information. Finally, there is the loss function from the three parts...
要点: 这篇论文通过基于Self Attention mechanism来捕获上下文依赖,并提出了Dual Attention Networks (DANet)来自适应地整合局部特征和全局依赖。该方法能够自适应地聚合长期上下文信息,从而提高了场景分割的特征表示。 组成: 在一贯的dilated FCN中加入两种类型地attention module。其中position attention module选择性地通过...
We will use the results of model reconstruction to prove that the dual attention mechanism makes the capsule pay more attention to the image information. Conv-attention module Figure 5 shows the principle of Conv-Attention. After the image is processed by ReLU Conv, the global pooling operation ...
In the branch of depth data processing network, the global spatial weight is established by using the attention mechanism of mask vector to realize robust extraction of depth features. In the phase of feature fusion, a symmetric fusion module is introduced. In this module, spatial features and ...
Sequence matching module是DuATM的最重要组成部分,特征序列提取模块得到的特征序列包含丰富的上下文信息,Sequence matching module 就是利用上下文信息通过attention mechanism帮助特征向量refinement(去除干扰帧的影响),特征序列对对齐。 特征序列对\left( X_{a}, X_{b}\right),其中X_{a} = \left\{ x_{a}^{i...
Li R, Zheng S, Duan C, et al. Classification of Hyperspectral Image Based on Double-Branch Dual-Attention Mechanism Network[J]. Remote Sensing, 2020, 12(3): 582. Requirements: numpy >= 1.16.5 PyTorch >= 1.3.1 sklearn >= 0.20.4 ...
By integrating KREN and the attention module into a single autoencoder, the accuracy on UCSD ped2 is further improved by 5.3%. The combination of a dual-channel autoencoder with the key region feature extraction network, incorporating the attention mechanism (KRFE-DAE), achieves the optimal ...
This method is built on the SE-ResNet50 based online abrasion state monitoring model and introduces an enhanced dual-attention mechanism to learn the dependency of pixel characteristics and the inter-correlation between channels, respectively. It is proposed that the Enhance Module Network capture the...
5.2.3 Attention Module Embedding with Networks 通过卷积层转换两个注意力模块的输出,并执行element-wise sum 完成特征融合。最后再做一次卷积得到最后的预测特征图。 5.3 Experiments 5.3.1 Ablation Study for Attention Modules 5.3.2 Ablation Study for Improvement Strategies Comparing with State-of-the-art发布...
In this paper, we propose a feature pyramid module (FPM) and global attention mechanism module (GAMM) for change detection in highresolution images. The proposed FPM is able to enrich semantic information in feature extraction procedure, and the proposed GAMM is capable of emphasizing difference ...