14 citations · 14 across the 5 of their papers we have counts for
5 papers
Towards Scalable GPU-Accelerated SNN Training via Temporal Fusion
Yanchen Li, Jiachun Li, Kebin Sun +2
Drawing on the intricate structures of the brain, Spiking Neural Networks (SNNs) emerge as a transformative development in artificial intelligence, closely emulating the complex dy…
Evolutionary Spiking Neural Networks: A Survey
Shuaijie Shen, Rui Zhang, Chao Wang +6
Spiking neural networks (SNNs) are gaining increasing attention as potential computationally efficient alternatives to traditional artificial neural networks(ANNs). However, the un…
Benchmarking Neural Decoding Backbones towards Enhanced On-edge iBCI Applications
Zhou Zhou, Guohang He, Zheng Zhang +5
Traditional invasive Brain-Computer Interfaces (iBCIs) typically depend on neural decoding processes conducted on workstations within laboratory settings, which prevents their ever…
Weakly-Supervised Action Localization by Hierarchically-structured Latent Attention Modeling
Guiqin Wang, Peng Zhao, Cong Zhao +5
Weakly-supervised action localization aims to recognize and localize action instancese in untrimmed videos with only video-level labels. Most existing models rely on multiple insta…
Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation
Yushun Tang, Ce Zhang, Heng Xu +5
Fully test-time adaptation aims to adapt the network model based on sequential analysis of input samples during the inference stage to address the cross-domain performance degradat…