Addressing the cold start problem in active learning using self-supervised learning
Active learning promises to improve annotation efficiency by iteratively selecting the most important data to be annotated first. However, we uncover a striking contrast to this promise: Active querying strategies fail to select data as effectively as random selection at the first choice. We identif...
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Format: | Final Year Project |
Language: | English |
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Nanyang Technological University
2022
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Online Access: | https://hdl.handle.net/10356/158461 |
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Institution: | Nanyang Technological University |
Language: | English |