4 citations · 7 across the 8 of their papers we have counts for
5 papers · 1 filter
SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge
Hao Ding, Yuqian Zhang, Tuxun Lu +39
Surgical data science has seen rapid advancement with the excellent performance of end-to-end deep neural networks (DNNs). Despite their successes, DNNs have been proven susceptibl…
Multi-objective Cross-task Learning via Goal-conditioned GPT-based Decision Transformers for Surgical Robot Task Automation
Jiawei Fu, Yonghao Long, Kai Chen +2
Surgical robot task automation has been a promising research topic for improving surgical efficiency and quality. Learning-based methods have been recognized as an interesting para…
SimEndoGS: Efficient Data-driven Scene Simulation using Robotic Surgery Videos via Physics-embedded 3D Gaussians
Zhenya Yang, Kai Chen, Yonghao Long +1
Surgical scene simulation plays a crucial role in surgical education and simulator-based robot learning. Traditional approaches for creating these environments with surgical scene…
Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training
Shizhan Gong, Qi Dou, Farzan Farnia
Gradient-based saliency maps have been widely used to explain the decisions of deep neural network classifiers. However, standard gradient-based interpretation maps, including the…
Efficient Physically-based Simulation of Soft Bodies in Embodied Environment for Surgical Robot
Zhenya Yang, Yonghao Long, Kai Chen +2
Surgical robot simulation platform plays a crucial role in enhancing training efficiency and advancing research on robot learning. Much effort have been made by scholars on develop…