Multi-scale attention mechanismWith the rapid increase of data availability, time series classification (TSC) has arisen in a wide range of fields and drawn great attention of researchers. Recently, hundreds of TSC approaches have been developed, which can be classified into two categories: ...
Based on U-Net, combined with multi-scale idea and attention mechanism, we designed a new segmentation model. We tested this method on the public datasets, calculated the segmentation metrics and compared several advanced semantic segmentation methods. The experimental results showed that our method ...
To address this problem, we adopt an attention mechanism to predict how to combine multi-scale predictions togetherat a pixel level, similar to the method proposed by Chen et. al. [1]. (1)We propose a hierarchical attention mechanismby which the network learns to predict a relative weighting...
adversarial trainingbearing fault diagnosismulti-scale convolutional kernelschannel attentionCONVOLUTIONAL NEURAL-NETWORKFor bearing fault diagnosis problems in ... H Peng,J Du,J Gao,... - 《Measurement Science & Technology》 被引量: 0发表: 2024年 Merge Multiscale Attention Mechanism MSGAN-ACNN-BiL...
(d_model,heads,self.d_k,bias=True)# Softmax for attention along the time dimension of `key`self.softmax=nn.Softmax(dim=1)self.output=nn.Linear(d_model,d_model)self.dropout=nn.Dropout(dropout_prob)self.scale=1/math.sqrt(self.d_k)# We store attentions so that it can ...
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。
The CRA block is introduced, which combines an attention mechanism with residual and skip connections to better capture multi-scale feature information and improve feature fusion, leading to increased awareness of general aspects and finer details. ...
CA-MCNN is a multi-scale convolutional neural network with the combination of pooling layers, efficient channel attention block and parallel feature fusion mechanism. We use the bearing dataset to find suitable pooling parameters and mini-batch size for the model, and verify the effectiveness of CA...
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...