ADL-GAN: Data Augmentation to Improve In-the-Wild ADL Recognition Using GANs
Author:
Affiliation:
1. Computer Science Department, Worcester Polytechnic Institute, Worcester, MA, USA
2. Biomedical Engineering Department, Worcester Polytechnic Institute, Worcester, MA, USA
Funder
Defense Advanced Research Projects Agency
High-Performance Computing System acquired through the National Science Foundation (NSF) Major Research Instrumentation Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
https://ieeexplore.ieee.org/ielam/6287639/10005208/10113320-aam.pdf
Reference46 articles.
1. A survey on generative adversarial networks for imbalance problems in computer vision tasks
2. Simultaneous Speech Recognition and Speaker Diarization for Monaural Dialogue Recordings with Target-Speaker Acoustic Models
3. A Systematic Review on Imbalanced Data Challenges in Machine Learning
4. Deep neural network-based speaker embeddings for end-to-end speaker verification
5. Unsupervised feature learning for environmental sound classification using Weighted Cycle-Consistent Generative Adversarial Network
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