SSL++ : Improving Self-Supervised Learning by Mitigating the Proxy Task-Specificity Problem
The success of deep convolutional networks (ConvNets) generally relies on a massive amount of well-labeled data, which is labor-intensive and time-consuming to collect and annotate in many scenarios. To eliminate such limitation, self-supervised learning (SSL) is recently proposed. Specifically, by...
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Bibliographische Detailangaben
Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 31(2022) vom: 21., Seite 1134-1148
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1. Verfasser: |
Chen, Song
(VerfasserIn) |
Weitere Verfasser: |
Xue, Jing-Hao,
Chang, Jianlong,
Zhang, Jianzhong,
Yang, Jufeng,
Tian, Qi |
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 |