End-to-End Polyphonic Sound Event Detection Using Convolutional Recurrent Neural Networks with Learned Time-Frequency Representation Input-Reference-Cited by-同舟云学术

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End-to-End Polyphonic Sound Event Detection Using Convolutional Recurrent Neural Networks with Learned Time-Frequency Representation Input

Published:2018-07 Issue: Volume: Page:
ISSN:
Container-title:2018 International Joint Conference on Neural Networks (IJCNN)
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Author:

Cakir Emre,Virtanen Tuomas

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8465565/8488986/08489470.pdf?arnumber=8489470

Cited by 9 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. Separation of overlapping audio signals: A review on current trends and evolving approaches;Signal Processing;2024-08

2. Automatic Multiple Sounds Detection with Recurrent Neural Networks (LSTM);Lecture Notes in Networks and Systems;2024

3. Hand-crafted versus learned representations for audio event detection;Multimedia Tools and Applications;2022-04-07

4. Master-Teacher-Student: A Weakly Labelled Semi-Supervised Framework for Audio Tagging and Sound Event Detection;IEICE Transactions on Information and Systems;2022-04-01

5. An Interpretable Deep Learning Model for Automatic Sound Classification;Electronics;2021-04-02

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