Sample-Centric Feature Generation for Semi-Supervised Few-Shot Learning
Semi-supervised few-shot learning aims to improve the model generalization ability by means of both limited labeled data and widely-available unlabeled data. Previous works attempt to model the relations between the few-shot labeled data and extra unlabeled data, by performing a label propagation or...
Ausführliche Beschreibung
Bibliographische Detailangaben
Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 31(2022) vom: 04., Seite 2309-2320
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1. Verfasser: |
Zhang, Bo
(VerfasserIn) |
Weitere Verfasser: |
Ye, Hancheng,
Yu, Gang,
Wang, Bin,
Wu, Yike,
Fan, Jiayuan,
Chen, Tao |
Format: | Online-Aufsatz
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Sprache: | English |
Veröffentlicht: |
2022
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Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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Schlagworte: | Journal Article |