A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification-Reference-Cited by-同舟云学术

A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification

Published:2023 Issue: Volume: Page:1-12
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Hong Qingqi¹^ORCID,Lin Lingli²,Li Zihan²^ORCID,Li Qingde³^ORCID,Yao Junfeng⁴^ORCID,Wu Qingqiang⁴,Liu Kunhong⁵^ORCID,Tian Jie⁶^ORCID

Affiliation:

1. Department of Digital Media Technology, Xiamen University, Xiamen, China

2. School of Informatics, Xiamen University, Xiamen, China

3. School of Computer Science, University of Hull, Hull, U.K.

4. School of Informatics, the Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism, and the School of Film, Xiamen University, Xiamen, China

5. School of Film, Xiamen University, Xiamen, China

6. Institute of Automation, CAS Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, China

Funder

Natural Science Foundation of Fujian Province of China

Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems, Beihang University

ITC-InnoHK Projects at Hong Kong Centre for Cerebro-Cardiovascular Health Engineering

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10145798.pdf?arnumber=10145798

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