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Found 5 papers, 2 papers with code
Arrhythmia Classification using CGAN-augmented ECG Signals
We employed two models for ECG generation: (i) unconditional GAN; Wasserstein GAN with gradient penalty (WGAN-GP) is trained on each class individually; (ii) conditional GAN; one Auxiliary Classifier WGAN-GP (AC-WGAN-GP) model is trained on all classes and then used to generate synthetic beats in all classes.
Synthetic ECG Signal Generation Using Generative Neural Networks
Electrocardiogram (ECG) datasets tend to be highly imbalanced due to the scarcity of abnormal cases.
FoleyGAN: Visually Guided Generative Adversarial Network-Based Synchronous Sound Generation in Silent Videos
Deep learning based visual to sound generation systems essentially need to be developed particularly considering the synchronicity aspects of visual and audio features with time.
AutoFoley: Artificial Synthesis of Synchronized Sound Tracks for Silent Videos with Deep Learning
AutoFoley can be used in the applications where there is either no corresponding audio file associated with the video or in cases where there is a need to identify critical scenarios and provide a synthesized, reinforced soundtrack.
Human Action Performance using Deep Neuro-Fuzzy Recurrent Attention Model
A great number of computer vision publications have focused on distinguishing between human action recognition and classification rather than the intensity of actions performed.
