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 ...
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 ...
We adopt a multi-scale attention method to each different layers in the U-net backbone to make the network extract features which focus on the crowds, instead of the background in the images. The attention mechanism and the skip-connections can adjust the weights of feature maps while ...
(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 ...
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 ...
(MFANet) based on deep learning, which integrates pyramid module and channel attention mechanism effectively. Pyramid module is designed for feature fusion in the channel and space dimensions. Channel attention mechanism obtains feature maps in different receptive fields, which divides each feature map ...
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。
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 attention mechanism 来学习每个像素位置的 softly weight the multi-scale features attention model 学习对于不同尺度的物体赋予不同的权重 对于提取多...
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 ...