Self-Supervised Learning of Audio Representations using Angular Contrastive Loss
Author:
Affiliation:
1. Tampere University,Computing Sciences,Tampere,Finland
Funder
Academy of Finland
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10094559/10094560/10094706.pdf?arnumber=10094706
Reference18 articles.
1. Understanding the Behaviour of Contrastive Loss
2. Self-Supervised Learning of Audio Representations From Audio-Visual Data Using Spatial Alignment
3. Data Augmentation Using Random Image Cropping and Patching for Deep CNNs
4. Understanding contrastive representation learning through alignment and uniformity on the hypersphere;wang;International Conference on Machine Learning,2020
5. Learning representations from audio-visual spatial alignment;morgado;Advances in neural information processing systems,2020
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1. The application of blood flow sound contrastive learning to predict arteriovenous graft stenosis of patients with hemodialysis;PLOS ONE;2024-08-16
2. Positive and Negative Sampling Strategies for Self-Supervised Learning on Audio-Video Data;2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW);2024-04-14
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