2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.CV2024★ 2 cited
Surgformer: Surgical Transformer with Hierarchical Temporal Attention for Surgical Phase Recognition
Shu Yang, Luyang Luo, Qiong Wang +1
Existing state-of-the-art methods for surgical phase recognition either rely on the extraction of spatial-temporal features at a short-range temporal resolution or adopt the sequen…
cs.CV2024★ 1 cited
SDiT: Spiking Diffusion Model with Transformer
Shu Yang, Hanzhi Ma, Chengting Yu +2
Spiking neural networks (SNNs) have low power consumption and bio-interpretable characteristics, and are considered to have tremendous potential for energy-efficient computing. How…