25 citations · 32 across the 2 of their papers we have counts for
3 papers
Bias-Free FedGAN: A Federated Approach to Generate Bias-Free Datasets
Vaikkunth Mugunthan, Vignesh Gokul, Lalana Kagal +1
Federated Generative Adversarial Network (FedGAN) is a communication-efficient approach to train a GAN across distributed clients without clients having to share their sensitive tr…
DPD-InfoGAN: Differentially Private Distributed InfoGAN
Vaikkunth Mugunthan, Vignesh Gokul, Lalana Kagal +1
Generative Adversarial Networks (GANs) are deep learning architectures capable of generating synthetic datasets. Despite producing high-quality synthetic images, the default GAN ha…
Deep Learning for Skin Lesion Classification
P. Mirunalini, Aravindan Chandrabose, Vignesh Gokul +1
Melanoma, a malignant form of skin cancer is very threatening to life. Diagnosis of melanoma at an earlier stage is highly needed as it has a very high cure rate. Benign and malign…