Frequency-Based Temporal Analysis Network for Accurate Phase Recognition from Surgical Videos-Reference-Cited by-同舟云学术

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Frequency-Based Temporal Analysis Network for Accurate Phase Recognition from Surgical Videos

Published:2024-05-27 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 IEEE International Symposium on Biomedical Imaging (ISBI)
language:
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Author:

Zhang Sainan¹,Xu Tianze¹,Cao Zhi¹,Liao Hongen²,Ning Guochen³,Chen Fang¹

Affiliation:

1. Nanjing University of Aeronautics and Astronautics,Department of Computer Science and Engineering,Nanjing,China

2. Tsinghua University,Department of Biomedical Engineering,Beijing,China,100084

3. Tsinghua University,School of Clinical Medicine,Beijing,China,100084

Funder

Nature

Research and Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635806.pdf?arnumber=10635806

Reference11 articles.

1. EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos

2. SV-RCNet: Workflow Recognition From Surgical Videos Using Recurrent Convolutional Network

3. Deep Residual Learning for Image Recognition

4. Multi-task recurrent convolutional network with correlation loss for surgical video analysis

5. TeCNO: Surgical Phase Recognition with Multi-stage Temporal Convolutional Networks

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