Acoustic Scene Classifier Based on Gaussian Mixture Model in the Concept Drift Situation-Reference-Cited by-同舟云学术

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Acoustic Scene Classifier Based on Gaussian Mixture Model in the Concept Drift Situation

Published:2021-09 Issue:5 Volume:6 Page:167-176
ISSN:2415-6698
Container-title:Advances in Science, Technology and Engineering Systems Journal
language:
Short-container-title:Adv. sci. technol. eng. syst. j.

Author:

Id Ibnu Daqiqil,Abe Masanobu,Hara Sunao

Publisher

ASTES Journal

Subject

Management of Technology and Innovation,Physics and Astronomy (miscellaneous),Engineering (miscellaneous)

Link

https://www.astesj.com/publications/ASTESJ_060519.pdf

Reference28 articles.

1. R. Elwell, R. Polikar, "Incremental Learning of Concept Drift in Nonstationary Environments," IEEE Transactions on Neural Networks, 22(10), 1517-1531, 2011, doi:10.1109/TNN.2011.2160459.

2. S. Ntalampiras, "Automatic analysis of audiostreams in the concept drift environment," in 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), IEEE, 2016, doi:10.1109/MLSP.2016.7738905.

3. J. Gama, I. Žliobait?, A. Bifet, M. Pechenizkiy, A. Bouchachia, "A Survey on Concept Drift Adaptation," ACM Computing Surveys, 46(4), 1-37, 2014, doi:10.1145/2523813.

4. T.R. Hoens, R. Polikar, N. V. Chawla, "Learning from Streaming Data with Concept Drift and Imbalance: An Overview," Progress in Artificial Intelligence, 1(1), 89-101, 2012, doi:10.1007/s13748-011-0008-0.

5. I. Žliobait?, "Learning under Concept Drift: an Overview," 1-36, 2010, doi:10.1002/sam.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Incremental acoustic scene classification using rehearsal-based strategy;2022 IEEE 11th Global Conference on Consumer Electronics (GCCE);2022-10-18

2. Concept drift adaptation for audio scene classification using high-level features;2022 IEEE International Conference on Consumer Electronics (ICCE);2022-01-07

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