Many studies show that convolutional neural networks can improve performance after embedding attention mechanism. However, the existing related research either develops more complex attention modules in pursuit of ultimate performance improvement; Or the performance improvement is not obvious in pursuit of ...
During the early days of attention mechanisms in computer vision, one paper published at CVPR 2018 (and TPAMI), Squeeze and Excitation Networks, introduced a novel channel attention mechanism. This simple yet efficient add-on module can be added to any baseline architecture to get an improvement ...
attention mechanism. This mechanism enables the network to capture deep spatio-temporal characteristics in a hierarchical manner and distinguish between different human movements in everyday life. Our investigations, using the UCI-HAR, WISDM, and IM-WSHA datasets, demonstrated that our proposed model, ...
Secondly, based on a local cross-channel interaction strategy, a lightweight efficient channel attention mechanism (LECA) is designed. The kernel size of 1D convolution is affected by channel number and coefficients. Multi-scale feature input is used to retain more detailed features of different ...
Channel-Attention U-Net: Channel Attention Mechanism for Semantic Segmentation of Esophagus and Esophageal Cancer 来自 科研支点 喜欢 0 阅读量: 268 作者:G Huang,J Zhu,J Li,Z Wang,J Zhou 摘要: The effective segmentation of esophagus and esophagus tumors from Computed Tomography (CT) images can ...
Recently, applying the attention mechanism to extract discriminative parts has become a trend. However, using the classical attention mechanism brings two main limitations in FGVC: First, they always focus on informative channels in feature maps but ignore those with poor information, which also ...
Additionally, we propose to equip a novel channel-wise attention mechanism based on the traditional generator of GAN to enhance the feature representation capability of deep network and extract more effective features. The mean absolute error (MAE) of Hounsfield Units (HU), peak signal-to-noise ...
Then, a multi-channel and multi-scale separable dilated convolution neural network with attention mechanism is proposed. The adopted separable dilated convolution increases the receptive fields of the convolution kernels and improves the calculation speed and accuracy of the model without increasing the ...
RIR allows abundant low-frequency information to be bypassed through multiple skip connections, making the main network focus on learning high-frequency information. Furthermore, we propose a channel attention mechanism to adaptively rescale channel-wise features by considering interdependencies among channel...
FcaNet: Frequency Channel Attention Networks Attention mechanism(注意机制),尤其是 channel attention(通道注意),在计算机视觉领域获得了巨大的成功。许多作品都关注如何设计高效的通道注意机制,而忽略了一个基本问题:使用全局平均池(GAP)作为毋庸置疑的预处理方法。 本次研究中,作者从不同的角度出发,利用频率分析重新思...