Graph convolutional neural networkmulti-scale attention mechanismEEGclassificationRecently, deep learning has been widely used in the classification of EEG signals and achieved satisfactory results. However, the correlation between EEG electrodes is rarely considered, which has been proved that there are ...
First, an attention mechanism block is introduced to construct a new type of residual block combination. Second, a multi-scale structure is constructed by choosing an appropriate convolution kernel size. Finally, the overall framework of MSA-ResNet is constructed for efficient training and failure ...
(1)We propose a hierarchical attention mechanismby which the network learns to predict a relative weighting between adjacent scales. In our method, because of it’shierarchical nature, we only require to augment the training pipeline with one extra scale whereas other methods suchas [1] require ...
On the basis of U-Net, we combined the ideas of multi-scale convolution module and attention mechanism to design a variety of innovative structures to improve its performance. At the same time, we mixed the binary cross-entropy loss function and the dice loss function in order to alleviate ...
Facial expression recognition based on multi-scale feature fusion and attention mechanism[J]. Microelectronics & Computer, 2022, 39(3): 34-40. DOI: 10.19304/J.ISSN1000-7180.2021.0799 Citation: SHI Hao, XING Yuhang, CHEN Lian. Facial expression recognition based on multi-scale feature fusion ...
We propose a novel network named Multi-scale Attention-Net with the dual attention mechanism to enhance the ability of feature representation for liver and tumors segmentation 我们提出了一种新的具有双重注意机制的多尺度注意网络,以增强肝脏和肿瘤分割的特征表示能力。
and CBAM65were tested on the NEU-DET dataset along with other attention mechanisms. The effect of using the attention mechanism is listed in Table6. Note that each of these approaches helped to reduce the computational complexity and parameter quantity of the model. Particularly, compared to the...
More specifically, MAResNet combines the bottom-up and top-down attention mechanisms and a state-of-the-art feed-forward network (ResNet), which is constructed by stacking attention modules that generate attention-aware features. In particular, the multi-scale attention mechanism is utilized at ...
To address those problems, we propose a multi-scale deformable convolution network with an attention mechanism (MsDCANet) to enhance the quality of underwater images. The proposed model is generally implemented by an encoder-decoder architecture. Concretely, we first propose a multi-scale deformable ...
语义分割--Attention to Scale: Scale-aware Semantic Image Segmentation /projects/DeepLab.html 针对语义分割问题,嵌入多尺度信息是很有必要的,这里我们提出用一个attentionmechanism 来学习每个像素位置的softly weight themulti-scalefeaturesattentionmodel学习对于不同尺度的物体赋予不同的权重 对于提取多尺度特征,目前主...