Shuijiao Chen

Orcid: 0000-0002-0111-3600

According to our database1, Shuijiao Chen authored at least 12 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
A graph-optimized deep learning framework for recognition of Barrett's esophagus and reflux esophagitis.
Multim. Tools Appl., November, 2024

Adaptify: A Refined Adaptation Scheme for Frame Classification in Atrophic Gastritis Videos.
CoRR, 2024

Adaptify: A Refined Test-Time Adaptation Scheme for Frame Classification Consistency in Atrophic Gastritis Videos.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Automated Scene Classification in Endoscopy Videos Using Convolutional Neural Networks.
Proceedings of the IEEE/ACM Conference on Connected Health: Applications, 2024

2023
MLMSA: Multi-Level and Multi-Scale Attention for Lesion Detection in Endoscopy.
Proceedings of the IEEE International Conference on E-health Networking, 2023

A CNN-Based Disease Detection Framework for Wireless Capsule Endoscopy Videos.
Proceedings of the IEEE International Conference on E-health Networking, 2023

2022
AFP-Mask: Anchor-Free Polyp Instance Segmentation in Colonoscopy.
IEEE J. Biomed. Health Informatics, 2022

Three feature streams based on a convolutional neural network for early esophageal cancer identification.
Multim. Tools Appl., 2022

MAF-Net: Multi-branch Anchor-Free Detector for Polyp Localization and Classification in Colonoscopy.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

2021
Detection of Endoscope Withdrawal Time in Colonoscopy Videos.
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Gastric Location Classification During Esophagogastroduodenoscopy Using Deep Neural Networks.
Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021

2020
Colorectal Polyp Detection in Real-world Scenario: Design and Experiment Study.
Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence, 2020


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