Multi-scale neural networkGramian Angular Field (GAF)Spatial attentionFeature fusionFault diagnosisAs one of the three major outdoor components of the railroad signal system, the track circuit plays an important role in ensuring the safety and efficiency of train operation. Therefore, when a fault ...
The COVID-19 pandemic has increasingly accelerated the publication pace of scientific literature. How to efficiently curate and index this large amount of biomedical literature under the current crisis is of great importance. Previous literature indexing
We propose an end-to-end deep learning network for medical image segmentation named Contextual Multi-Scale Multi-Level Network (CMM-Net). The main idea of our CMM-Net is to generate global multi-level contextual information at every encoder convolutional level, which allows the network to learn ...
使用multi-scale detection features进行多次上采样得到center heatmap。 [2021] TransMOT: Spatial-Temporal Graph Transformer for Multiple Object Tracking 本文首先分析了当前transtrack, trackformer这种基于transformer的MOT方法效果还不够好的原因,一个是目标太多,但是却没有显式的去表示目标之间的spatial-temporal 结构...
Attention Network for no-reference Image Quality Assessment (MANIQA) to improve the performance on GAN-based distortion. We firstly extract features via ViT, then to strengthen global and local interactions, we propose the Transposed Attention Block (TAB) and the Scale Swin Transformer Block (SSTB...
Previous studies have revealed large-scale improvements in data coverage and measurement fidelity to track dynamic changes in RNA transcripts, ribosome profiling, proteins, and metabolites quantitatively in unprecedented detail125,126,127. Multi-omics studies provide the potential for a more holistic pictur...
In the following subsections, we review analysis techniques for the detection of mesoscale structure in brain networks, focusing on communities due to their inherent multi-scale nature. We pay particular attention to techniques that make it possible to detect community structure over a range of topol...
, 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings (2015) http://arxiv.org/abs/1409.0473 Google Scholar [150] Putelli L., Gerevini A.E., Lavelli A., Serina I. Applying self-interaction attention for ...
Multiscale spatial attention in Siamese network In our work, we input the features of the last three layers of ResNet-50 of both template and search feature map into the SAE block. As shown in the right side of Fig.3, we can get two multiscale spatial attention features for template and...
Paper tables with annotated results for MuSLCAT: Multi-Scale Multi-Level Convolutional Attention Transformer for Discriminative Music Modeling on Raw Waveforms