most citedEnhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation

5 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

cs.MM20243 cited

Spiking Tucker Fusion Transformer for Audio-Visual Zero-Shot Learning

Wenrui Li, Penghong Wang, Ruiqin Xiong +1

The spiking neural networks (SNNs) that efficiently encode temporal sequences have shown great potential in extracting audio-visual joint feature representations. However, coupling…

cs.NI2024

DV-Hop localization based on Distance Estimation using Multinode and Hop Loss in WSNs

Penghong Wang, Xingtao Wang, Wenrui Li +2

Location awareness is a critical issue in wireless sensor network applications. For more accurate location estimation, the two issues should be considered extensively: 1) how to su…

cs.NI20243 cited

Probability-based Distance Estimation Model for 3D DV-Hop Localization in WSNs

Penghong Wang, Hao Wang, Wenrui Li +2

Localization is one of the pivotal issues in wireless sensor network applications. In 3D localization studies, most algorithms focus on enhancing the location prediction process, l…

cs.CV2023

Deep Unfolding Network for Image Compressed Sensing by Content-adaptive Gradient Updating and Deformation-invariant Non-local Modeling

Wenxue Cui, Xiaopeng Fan, Jian Zhang +1

Inspired by certain optimization solvers, the deep unfolding network (DUN) has attracted much attention in recent years for image compressed sensing (CS). However, there still exis…

eess.SP20233 cited

Spiking Semantic Communication for Feature Transmission with HARQ

Mengyang Wang, Jiahui Li, Mengyao Ma +1

In Collaborative Intelligence (CI), the Artificial Intelligence (AI) model is divided between the edge and the cloud, with intermediate features being sent from the edge to the clo…

cs.NE20235 cited

Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation

Chenlin Zhou, Han Zhang, Zhaokun Zhou +5

Deep spiking neural networks (SNNs) have drawn much attention in recent years because of their low power consumption, biological rationality and event-driven property. However, sta…