Multi-scale attention mechanismSelective dense feature connectionsThe success of deep learning has brought breakthroughs in many fields. However, the increased performance of deep learning models is often accompanied by an increase in their depth and width, which conflicts with the storage, energy ...
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 ...
Attention mechanism can improve the ability of networks to suppress useless information. It does not require significant changes to the network architecture and only needs to introduce a small number of parameters to obtain higher accuracy. Oktay et al. [4] introduced a soft attention mechanism and...
(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 ...
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。
MA-Unet: An improved version of Unet based on multi-scale and attention mechanism for medical image segmentation 来自 arXiv.org 喜欢 0 阅读量: 1151 作者:Y Cai,Y Wang 摘要: Although convolutional neural networks (CNNs) are promoting the development of medical image semantic segmentation, the ...
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 ...
Southeast University Researcher Illuminates Research in Pattern Recognition and Artificial Intelligence (Graph Convolutional Neural Network with Multi-Scale Attention Mechanism for EEG-Based Motion Imagery Classification) 来自 掌桥科研 喜欢 0 阅读量: 9 摘要: By a News Reporter-Staff News Editor at ...
(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 ...
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 ...