The Effectiveness of Data Augmentation for Detection of Gastrointestinal Diseases from Endoscopical Images-Reference-Cited by-同舟云学术

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The Effectiveness of Data Augmentation for Detection of Gastrointestinal Diseases from Endoscopical Images

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies
language:
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Author:

Asperti Andrea¹,Mastronardo Claudio¹

Affiliation:

1. University of Bologna, Italy

Publisher

SCITEPRESS - Science and Technology Publications

Cited by 22 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. Automated identification of gastric cancer in endoscopic images by a deep learning model;Automatika;2024-02-07

2. LWU-Net approach for Efficient Gastro-Intestinal Tract Image Segmentation in Resource-Constrained Environments;2023-12-05

3. Multi-classification deep learning models for detection of ulcerative colitis, polyps, and dyed-lifted polyps using wireless capsule endoscopy images;Complex & Intelligent Systems;2023-11-24

4. Characterisation of Data Augmentation Techniques Using Visualisation;2023 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET);2023-09-12

5. A Comprehensive Analysis of Deep Learning-Based Approaches for the Prediction of Gastrointestinal Diseases Using Multi-class Endoscopy Images;Archives of Computational Methods in Engineering;2023-06-15

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