1 citations · 3 across the 4 of their papers we have counts for
5 papers
Revisiting Distribution Matching for State-to-Vision Policy Distillation in Laparoscopic Robotic Manipulation
Mingyu Sheng, Jianan Fan, Dongnan Liu +3
End-to-end control policies trained via Reinforcement Learning (RL) have emerged as an alternative to conventional surgical robotic control approaches, with recent studies explorin…
SurgiATM: A Physics-Guided Plug-and-Play Model for Deep Learning-Based Smoke Removal in Laparoscopic Surgery
Mingyu Sheng, Jianan Fan, Dongnan Liu +3
During laparoscopic surgery, smoke generated by tissue cauterization can significantly degrade the visual quality of endoscopic frames, increasing the risk of surgical errors and h…
Tab2Visual: Overcoming Limited Data in Tabular Data Classification Using Deep Learning with Visual Representations
Ahmed Mamdouh, Moumen El-Melegy, Samia Ali +1
This research addresses the challenge of limited data in tabular data classification, particularly prevalent in domains with constraints like healthcare. We propose Tab2Visual, a n…
AMNCutter: Affinity-Attention-Guided Multi-View Normalized Cutter for Unsupervised Surgical Instrument Segmentation
Mingyu Sheng, Jianan Fan, Dongnan Liu +2
Surgical instrument segmentation (SIS) is pivotal for robotic-assisted minimally invasive surgery, assisting surgeons by identifying surgical instruments in endoscopic video frames…
Revisiting Surgical Instrument Segmentation Without Human Intervention: A Graph Partitioning View
Mingyu Sheng, Jianan Fan, Dongnan Liu +2
Surgical instrument segmentation (SIS) on endoscopic images stands as a long-standing and essential task in the context of computer-assisted interventions for boosting minimally in…