High Accuracy Patch-Level Classification of Wireless Capsule Endoscopy Images Using a Convolutional Neural Network
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/8754684/8759097/08759324.pdf?arnumber=8759324
Cited by 12 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. Deep learning-enabled detection and localization of gastrointestinal diseases using wireless-capsule endoscopic images;Biomedical Signal Processing and Control;2024-07
2. Classification of images using INCEPTION algorithm in comparison with VGG-19 algorithm to measure accuracy;AIP Conference Proceedings;2024
3. GastroNet: A robust attention‐based deep learning and cosine similarity feature selection framework for gastrointestinal disease classification from endoscopic images;CAAI Transactions on Intelligence Technology;2023-06-11
4. Computer vision-based solutions to overcome the limitations of wireless capsule endoscopy;Journal of Medical Engineering & Technology;2023-05-19
5. Improved Water Strider Optimization with Deep Learning based Image Classification for Wireless Capsule Endoscopy;2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS);2023-02-02
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