159 citations
- California Institute of TechnologyUS3 papers
- Johns Hopkins UniversityUS3 papers
- University College LondonGB3 papers
- University of British ColumbiaCA3 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Imperial College LondonGB2 papers
- Indian Institute of Technology KharagpurIN2 papers
- Institut de Chirurgie Guidée par l'ImageFR2 papers
- Université de StrasbourgFR2 papers
- Wellcome / EPSRC Centre for Interventional and Surgical SciencesGB2 papers
- Agostino Gemelli University PolyclinicIT1 paper
- Auburn UniversityUS1 paper
Showing 2020Show all
3 papers · 1 filter
cs.LG2020★ 15 cited
Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and Algorithms
Aaron J. Snoswell, Surya P. N. Singh, Nan Ye
We provide new perspectives and inference algorithms for Maximum Entropy (MaxEnt) Inverse Reinforcement Learning (IRL), which provides a principled method to find a most non-commit…
cs.CV2020★ 3 cited
daVinciNet: Joint Prediction of Motion and Surgical State in Robot-Assisted Surgery
Yidan Qin, Seyedshams Feyzabadi, Max Allan +2
This paper presents a technique to concurrently and jointly predict the future trajectories of surgical instruments and the future state(s) of surgical subtasks in robot-assisted s…
cs.CV2020★ 9 cited
Temporal Segmentation of Surgical Sub-tasks through Deep Learning with Multiple Data Sources
Yidan Qin, Sahba Aghajani Pedram, Seyedshams Feyzabadi +4
Many tasks in robot-assisted surgeries (RAS) can be represented by finite-state machines (FSMs), where each state represents either an action (such as picking up a needle) or an ob…