WCE‐DCGAN: A data augmentation method based on wireless capsule endoscopy images for gastrointestinal disease detection-Reference-Cited by-同舟云学术

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WCE‐DCGAN: A data augmentation method based on wireless capsule endoscopy images for gastrointestinal disease detection

Published:2022-12-03 Issue:4 Volume:17 Page:1170-1180
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Xiao Zhiguo¹,Lu Jia²^ORCID,Wang Xiaokun³,Li Nianfeng¹,Wang Yuying⁴,Zhao Nan²

Affiliation:

1. College of Computer Science and Technology Changchun University Changchun China

2. School Cuber Security, Changchun University ChangchunChina

3. Operations Service College Air Force Aviation University Changchun China

4. School of Cyber Security Changchun University Changchun China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ipr2.12704

Reference41 articles.

1. Quantitative analysis of patients with celiac disease by video capsule endoscopy: A deep learning method

2. A New Automated Polyp Detection Network MP-FSSD in WCE and Colonoscopy Images Based Fusion Single Shot Multibox Detector and Transfer Learning

3. Deep learning for wireless capsule endoscopy: a systematic review and meta-analysis

4. Chen H. Chen J. Peng Q. et al.:Automatic hookworm image detection for wireless capsule endoscopy using hybrid color gradient and contourlet transform. In:2013 6th International Conference on Biomedical Engineering and Informatics. Hangzhou China. pp.116–120(2013)

5. Fu Y. Mandal M. Guo G.:Bleeding region detection in WCE images based on color features and neural network. In:2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS). Seoul Korea. pp.1–4(2011)

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3. Color-Transfer-Enhanced Data Construction and Validation for Deep Learning-Based Upper Gastrointestinal Landmark Classification in Wireless Capsule Endoscopy;Diagnostics;2024-03-11

4. Efficient-gastro: optimized EfficientNet model for the detection of gastrointestinal disorders using transfer learning and wireless capsule endoscopy images;PeerJ Computer Science;2024-03-11

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