Attention mechanismTo detect the targets of different sizes, multi-scale output is used by target detectors such as YOLO V3 and DSSD. To improve the detection performance, YOLO V3 and DSSD perform feature fusion by combining two adjacent scales. However, the feature fusion only between the ...
Fine-Grained Detection Model Based on Attention Mechanism and Multi-Scale Feature Fusion for Cocoon Sorting To deal with this problem, an efficient fine-grained object detection network based on attention mechanism and multi-scale feature fusion, called AMMF-Net... H Zheng,X Guo,Y Ma,... 被...
该预测部分由两个系列计算组成,首先先计算基本部分: 作者先提取了每层 Attention 的权重,也就是最后乘 V 之前,之后由于是 Multi-head,为了保留所有特征,方法选取将每个端口的权重图相乘: L 为层数;K 为 Multi-head 数量;C 为通道数;这公式着实写的不是很精致 之后将这些 A 连接在一起,大小就为 L*N,即下...
Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration - ziyueqingwan/LocalGlobalAttention
The SWFC module evenly distributes semantic features for each feature layer and the GC block introduces a self-attention mechanism. As a feature pyramid network, the CATFPN can be applied to any detector based on multi-scale features. We adopt the CATFPN in typical RetinaNet and Faster R-CNN...
1,集成了H.265标准参考软件HM的拟议高效视频编码系统(EVCS)可以实现12.141%的比特率节省,其性能优于基于深度学习的压缩视频恢复工作。 此外,EVCS可以轻松地与所有现有视频编解码器兼容,而无需修改其内核。 2,我们提出了多尺度通道注意(MSCA)机制,以提取不同尺度的特征并通过考虑特征通道之间的相关性来自适应地重新缩...
To better characterize the spatial similarity at the boundary of spatial domains, STAGATE adopts an attention mechanism to adaptively learn the similarity of neighboring spots, and an optional cell type-aware module through integrating the pre-clustering of gene expressions. We validate STAGATE on ...
Swin-Transformer’s self-attention mechanism, which hinges on input sequences, may falter with significant target deformations or camera-induced positional shifts, impacting tracking performance. Conversely, ToMP50’s ResNet backbone adeptly captures local image details, adapting well to deformations and ...
context and attention mechanism multiscale training and testing training strategy and loss function feature fusion and enhancement better proposal and balance 现在SOTA 由 两阶段方法占据。 介绍下 Anchor-based 的 one-stage 方法的 SSD? SSD 计算效率高。 SSD spreads out anchor boxes on multi-scale layer...
Spectral–Spatial Large Kernel Attention Network for Hyperspectral Image Classification Hyperspectral imagingConvolutional neural networksTask analysisImage classificationDue to its ability to capture long-range dependencies, self-attention mechanism-... C Wu,L Tong,J Zhou,... - 《IEEE Transactions on Geos...