Bibliographische Detailangaben
| Titel: |
ActiveSleepLearner: Less Annotation Budget for Better Large-Scale Sleep Staging |
| Autoren: |
Qi Liu, Jie Wei, Thomas Penzel, Maarten De Vos, Yuan Zhang, Zhiyi Huang, Mikhail Poluektov, Yulan Zhu, Chenyu Li |
| Quelle: |
IEEE Transactions on Emerging Topics in Computational Intelligence. 9:1756-1765 |
| Verlagsinformationen: |
Institute of Electrical and Electronics Engineers (IEEE), 2025. |
| Publikationsjahr: |
2025 |
| Schlagwörter: |
Optimization, Brain modeling, Technology, Science & Technology, STADIUS-24-132, Complexity theory, transfer learning, Computer Science, Artificial Intelligence, Transfer learning, 4603 Computer vision and multimedia computation, Sleep staging, 4611 Machine learning, active learning, Computer Science, Annotations, Feature extraction, Sleep |
| Beschreibung: |
sponsorship: This work was supported in part by the National Natural Science Foundation of China under Grant 62471407 and Grant 62172340, in part by Chongqing Medical Scientific Research General Project (Joint Project of Chongqing Health Commission and Science and Technology Bureau, under Grant 2024MSXM133), in part by Flemish Government (AI Research Program), and in part by FWO through Research Project 'Artificial Intelligence (AI) for Data-Driven Personalised Medicine' under Grant G0C9623N. (National Natural Science Foundation of China|62471407, National Natural Science Foundation of China|62172340, Chongqing Medical Scientific Research General Project (Joint Project of Chongqing Health Commission and Science and Technology Bureau)|2024MSXM133, Flemish Government (AI Research Program), FWO|G0C9623N) |
| Publikationsart: |
Article |
| ISSN: |
2471-285X |
| DOI: |
10.1109/tetci.2024.3446389 |
| Rights: |
IEEE Copyright |
| Dokumentencode: |
edsair.doi.dedup.....f43c46db6bcbbbadecf0d0c9db2d0bfa |
| Datenbank: |
OpenAIRE |
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