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Few-shot bioacoustic event detection is a task that detects the occurrence time of a novel sound given a few examples.
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2020
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P. Rodríguez, I. Laradji, A. Drouin, and A. Lacoste, “Embedding propagation: Smoother manifold for few-shot classification,” in
2020
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Q. Kong, Y. Cao, T. Iqbal, Y. Wang, W. Wang, and M. D. Plumbley, “Panns: Large-scale pretrained audio neural networks for audio pattern recognition,”
2020
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H. Liu, L. Xie, J. Wu, and G. Yang, “Channel-wise subband input for better voice and accompaniment separation on high resolution music,”
2020
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2020
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V. Morfi, I. Nolasco, V. Lostanlen, S. Singh, A. Strandburg-Peshkin, L. F. Gill, H. Pamula, D. Benvent, and D. Stowell, “Few-shot bioacoustic event detection: A new task at the dcase 2021 challenge.” in
2021
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Y. Gong, Y.-A. Chung, and J. Glass, “Psla: Improving audio tagging with pretraining, sampling, labeling, and aggregation,”
2021
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M. Boudiaf, H. Kervadec, Z. I. Masud, P. Piantanida, I. Ben Ayed, and J. Dolz, “Few-shot segmentation without meta-learning: A good transductive inference is all you need?” in
2021
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A. Mesaros, T. Heittola, T. Virtanen, and M. D. Plumbley, “Sound event detection: A tutorial,”
2021
Cited alongside, same era.
T. Tang, Y. Liang, and Y. Long, “Two improved architectures based on prototype network for few-shot bioacoustic event detection,” DCASE2021 Challenge, Tech. Rep., 2021
2021
Cited alongside, same era.
Y. Zhang, J. Wang, D. Zhang, and F. Deng, “Few-shot bioacoustic event detection using prototypical network with background classs,” DCASE2021 Challenge, Tech. Rep., 2021
2021
Cited alongside, same era.
2021
Cited alongside, same era.
2021
Later among the works it cites.
2021
Later among the works it cites.
D. Yang, H. Wang, Y. Zou, Z. Ye, and W. Wang, “A mutual learning framework for few-shot sound event detection,” in
2022
Closest in time.
H. Liu, X. Liu, X. Mei, Q. Kong, W. Wang, and M. D. Plumbley, “Surrey system for dcase 2022 task 5 : Few-shot bioacoustic event detection with segment-level metric learning,” DCASE2022 Challenge, Tech. Rep., 2022
2022
Closest in time.
J. Tang, Z. Xueyang, T. Gao, D. Liu, X. Fang, J. Pan, Q. Wang, J. Du, K. Xu, and Q. Pan, “Few-shot embedding learning and event filtering for bioacoustic event detection,” DCASE2022 Challenge, Tech. Rep., 2022
2022
Closest in time.