To address the issues above, we propose a multi-branch attention and alignment network (MAAN). This approach is based on a deep network with three main branches. One branch is used for global feature representations. Another branch implements a multi-attention process based on keypoints, filters...
To this end, a Multi-Branch Attention Network (MBA-Net) is proposed to achieve multi-level refinement of features through an end-to-end multi-branch framework with attention mechanisms. Specifically, we first achieve preliminary feature refinement through a backbone network with a non-local ...
Local Residual Attention Network (LRAN), that improves the predictive performance of a base-network by attending to class relevant regions of an image. LRA... R Subramanyam 被引量: 0发表: 2022年 ADBNet: An Attention-Guided Deep Broad Convolutional Neural Network for the Classification of Breast...
通常情况下,h \times w远大于D,因此 T-MSA 比 MSA 更适用于测试高分辨率图像,并且保证了值与 MSA 接近。 多尺度注意力优化(Multi-scale Attention Refinement) 首先,为了降低计算复杂度,我们使用一阶泰勒展开对 softmax 进行近似,并忽略了Peano剩余项的形式,这样就产生了必然的近似误差。然而,对于多头自注意力机...
Research on emotion recognition is an interesting area because of its wide-ranging applications in education, marketing, and medical fields. This study proposes a multi-branch convolutional neural network model based on cross-attention mechanism (MCNN-CA) for accurate recognition of different emotions....
F_{attention-I} , F_{attention-P} 为注意力权重(attention maps)表示图像和点的相对重要性。 Hybrid Sampling Strategy 混合采样策略 在SA层中,我们需要对点进行下采样以扩大感受野。点云在空间上是无序的。为了保证采样的均匀性,通常使用FPS尽可能覆盖整个空间。然而,FPS只考虑了点之间的相对距离,而没有利用...
Deep network attracts extensive attention in the single image super-resolution field. Most of the deep network-based super-resolution methods usually emplo... D Li,S Yang,X Wang,... - 《Digital Signal Processing》 被引量: 0发表: 2024年 Residual multi-branch distillation network for efficient...
摘要: Recently, advances in person re-identification (Re-ID) has benefitted from use of the popular multi-branch network. However, performing feature learning in a single branch with uniform partitioning...关键词: Person re-identification pooling strategy attention mechanism triplet loss ...
Built-up area is one of the most important objects of remote sensing images analysis, therefore extracting built-up area from remote sensing image automatically has attracted wide attention. It is common to treat built-up area extraction as image segmentation task. However, it's hard to devise ...
In this paper, we describe in detail our systems for DCASE 2020 Task 4. The systems are based on the 1st-place system of DCASE 2019 Task 4, which adopts weakly-supervised framework with an attention-based embedding-level multiple instance learning pooling module and a semi-supervised learning ...