One to Many: Adaptive Instrument Segmentation via Meta Learning and Dynamic Online Adaptation in Robotic Surgical Video-Reference-Cited by-同舟云学术

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One to Many: Adaptive Instrument Segmentation via Meta Learning and Dynamic Online Adaptation in Robotic Surgical Video

Published:2021-05-30 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Zhao Zixu,Jin Yueming,Lu Bo,Ng Chi-Fai,Dou Qi,Liu Yun-Hui,Heng Pheng-Ann

Funder

Research and Development

National Natural Science Foundation of China

Shun Hing Institute of Advanced Engineering

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9560720/9560666/09561690.pdf?arnumber=9561690

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. LLM-Assisted Multi-Teacher Continual Learning for Visual Question Answering in Robotic Surgery;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

2. Long-short diffeomorphism memory network for weakly-supervised ultrasound landmark tracking;Medical Image Analysis;2024-05

3. Scaling While Privacy Preserving: A Comprehensive Synthetic Tabular Data Generation and Evaluation in Learning Analytics;Proceedings of the 14th Learning Analytics and Knowledge Conference;2024-03-18

4. Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art;Computers in Biology and Medicine;2024-02

5. Visual-Kinematics Graph Learning for Procedure-Agnostic Instrument Tip Segmentation in Robotic Surgeries;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

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