Refining the Unseen: Self-supervised Two-stream Feature Extraction for Image Quality Assessment-Reference-Cited by-同舟云学术

Refining the Unseen: Self-supervised Two-stream Feature Extraction for Image Quality Assessment

Published:2023-12-01 Issue: Volume: Page:1193-1198
ISSN:
Container-title:2023 IEEE International Conference on Data Mining (ICDM)
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Author:

Lou Yiwei¹,Chen Yanyuan²,Xu Dexuan²,Zhou Doudou³,Cao Yongzhi¹,Wang Hanpin¹,Huang Yu⁴

Affiliation:

1. Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education; School of Computer Science, Peking University,Beijing,China

2. Peking University,School of Software & Microelectronics,Beijing,China

3. Harvard T.H. Chan School of Public Health,Department of Biostatistics,Boston,USA

4. Peking University,National Engineering Research Center for Software Engineering,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10415628/10415561/10415683.pdf?arnumber=10415683

Reference37 articles.

1. MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment

2. Machine learning to predict clinical remission in depressed patients after acute phase selective serotonin reuptake inhibitor treatment

3. Perceptual image quality assessment: a survey

4. Multi-task Fundus Image Quality Assessment via Transfer Learning and Landmarks Detection

5. TTL-IQA: Transitive Transfer Learning Based No-Reference Image Quality Assessment

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