An X-ray image classification method with fine-grained features for explainable diagnosis of pneumoconiosis-Reference-Cited by-同舟云学术

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An X-ray image classification method with fine-grained features for explainable diagnosis of pneumoconiosis

Published:2023-06-22 Issue: Volume: Page:
ISSN:1617-4909
Container-title:Personal and Ubiquitous Computing
language:en
Short-container-title:Pers Ubiquit Comput

Author:

Zhang Chunmei,He Jia,Shang Lin

Publisher

Springer Science and Business Media LLC

Subject

Management Science and Operations Research,Computer Science Applications,Hardware and Architecture,Library and Information Sciences

Link

https://link.springer.com/content/pdf/10.1007/s00779-023-01730-3.pdf

Reference48 articles.

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2. Zhang D, Yin J, Zhu X, Zhang C (2018) Network representation learning: a survey. IEEE transactions on Big Data 6(1):3–28

3. Wang Z, Du B, Guo Y (2019) Domain adaptation with neural embedding matching. IEEE transactions on neural networks and learning systems 31(7):2387–2397

4. Arevalo J, González FA, Ramos-Pollán R, Oliveira JL, Lopez MAG (2016) Representation learning for mammography mass lesion classification with convolutional neural networks. Computer methods and programs in biomedicine 127:248–257

5. Frid-Adar, M., Klang, E., Amitai, M., Goldberger, J., Greenspan, H.: Synthetic data augmentation using gan for improved liver lesion classification. In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), pp. 289–293 (2018). IEEE

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1. X-ray body Part Classification Using Custom CNN;EAI Endorsed Transactions on Pervasive Health and Technology;2024-03-28

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