Multi-level fusion based class-aware attention model for weakly labeled audio tagging
10.1145/3343031.3351090
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sg-nus-scholar.10635-2007262023-09-08T09:16:46Z Multi-level fusion based class-aware attention model for weakly labeled audio tagging Yin, Y Shrivastava, H Chiou, MJ Shah, RR Liu, Z Zimmermann, R CHEMICAL & BIOMOLECULAR ENGINEERING 10.1145/3343031.3351090 MM '19: The 27th ACM International Conference on Multimedia 1304-1312 2021-09-20T07:45:52Z 2021-09-20T07:45:52Z 2019-10-15 2021-09-19T15:20:28Z Conference Paper Yin, Y, Shrivastava, H, Chiou, MJ, Shah, RR, Liu, Z, Zimmermann, R (2019-10-15). Multi-level fusion based class-aware attention model for weakly labeled audio tagging. MM '19: The 27th ACM International Conference on Multimedia : 1304-1312. ScholarBank@NUS Repository. https://doi.org/10.1145/3343031.3351090 9781450368896 https://scholarbank.nus.edu.sg/handle/10635/200726 ACM Elements |
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10.1145/3343031.3351090 |
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CHEMICAL & BIOMOLECULAR ENGINEERING |
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CHEMICAL & BIOMOLECULAR ENGINEERING Yin, Y Shrivastava, H Chiou, MJ Shah, RR Liu, Z Zimmermann, R |
format |
Conference or Workshop Item |
author |
Yin, Y Shrivastava, H Chiou, MJ Shah, RR Liu, Z Zimmermann, R |
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Yin, Y Shrivastava, H Chiou, MJ Shah, RR Liu, Z Zimmermann, R Multi-level fusion based class-aware attention model for weakly labeled audio tagging |
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Yin, Y |
title |
Multi-level fusion based class-aware attention model for weakly labeled audio tagging |
title_short |
Multi-level fusion based class-aware attention model for weakly labeled audio tagging |
title_full |
Multi-level fusion based class-aware attention model for weakly labeled audio tagging |
title_fullStr |
Multi-level fusion based class-aware attention model for weakly labeled audio tagging |
title_full_unstemmed |
Multi-level fusion based class-aware attention model for weakly labeled audio tagging |
title_sort |
multi-level fusion based class-aware attention model for weakly labeled audio tagging |
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ACM |
publishDate |
2021 |
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https://scholarbank.nus.edu.sg/handle/10635/200726 |
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1779154096053288960 |