Real-Time and High-Accuracy Switchable Stereo Depth Estimation Method Utilizing Self-Supervised Online Learning Mechanism for MIS-Reference-Cited by-同舟云学术

Real-Time and High-Accuracy Switchable Stereo Depth Estimation Method Utilizing Self-Supervised Online Learning Mechanism for MIS

Published:2024 Issue: Volume:73 Page:1-13
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Zheng Jieyu¹^ORCID,Li Xiaojian¹^ORCID,Wang Xin²^ORCID,Wu Haojun²^ORCID,Li Ling¹^ORCID,Ma Xiang¹^ORCID,Yang Shanlin¹^ORCID

Affiliation:

1. School of Management, Key Laboratory of Process Optimization and Intelligent Decision-Making, and the Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance, Ministry of Education, Hefei University of Technology, Hefei, China

2. Department of General Surgery, West China Hospital, Division of Pancreatic Surgery and the Division of Biliary Surgery, Sichuan University, Chengdu, Sichuan, China

Funder

National Natural Science Foundation of China

Anhui Provincial Natural Science Foundation

Anhui Provincial Major Science and Technology Project

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/19/10367905/10623422.pdf?arnumber=10623422

Reference35 articles.

1. SFF-DA: Spatiotemporal Feature Fusion for Nonintrusively Detecting Anxiety

2. Dense Depth Estimation in Monocular Endoscopy With Self-Supervised Learning Methods

3. Real-Time Dense Reconstruction of Tissue Surface From Stereo Optical Video

4. Artificial intelligence and automation in endoscopy and surgery

5. FRSR: Framework for real-time scene reconstruction in robot-assisted minimally invasive surgery