CNN-RNN and Data Augmentation Using Deep Convolutional Generative Adversarial Network for Environmental Sound Classification
Author:
Affiliation:
1. School of Mechatronics System Engineering, Simon Fraser University, Surrey, BC, Canada
2. Faculty of Education, Simon Fraser University, Burnaby, BC, Canada
Funder
Kids Brain Health Network
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/97/9686799/09717998.pdf?arnumber=9717998
Reference39 articles.
1. Unsupervised feature learning for environmental sound classification using Weighted Cycle-Consistent Generative Adversarial Network
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4. spectral analysis and discrimination by zero-crossings;kedem;Proceedings of the IEEE,1986
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