3 papers
cs.LG2026
Towards Green Wearable Computing: A Physics-Aware Spiking Neural Network for Energy-Efficient IMU-based Human Activity Recognition
Naichuan Zheng, Hailun Xia, Zepeng Sun +2
Wearable IMU-based Human Activity Recognition (HAR) relies heavily on Deep Neural Networks (DNNs), which are burdened by immense computational and buffering demands. Their power-hu…
cs.CV2026
S3T-Former: A Purely Spike-Driven State-Space Topology Transformer for Skeleton Action Recognition
Naichuan Zheng, Hailun Xia, Zepeng Sun +2
Skeleton-based action recognition is crucial for multimedia applications but heavily relies on power-hungry Artificial Neural Networks (ANNs), limiting their deployment on resource…
cs.CV2025
Signal-SGN++: Topology-Enhanced Time-Frequency Spiking Graph Network for Skeleton-Based Action Recognition
Naichuan Zheng, Xiahai Lun, Weiyi Li +1
Graph Convolutional Networks (GCNs) demonstrate strong capability in modeling skeletal topology for action recognition, yet their dense floating-point computations incur high energ…