293 citations · 1.2k across the 76 of their papers we have counts for
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Learned Half-Quadratic Splitting Network for MR Image Reconstruction
Bingyu Xin, Timothy S. Phan, Leon Axel +1
Magnetic Resonance (MR) image reconstruction from highly undersampled -space data is critical in accelerated MR imaging (MRI) techniques. In recent years, deep learning-based me…
AE-StyleGAN: Improved Training of Style-Based Auto-Encoders
Ligong Han, Sri Harsha Musunuri, Martin Renqiang Min +3
StyleGANs have shown impressive results on data generation and manipulation in recent years, thanks to its disentangled style latent space. A lot of efforts have been made in inver…
Stochastic Transformer Networks with Linear Competing Units: Application to end-to-end SL Translation
Andreas Voskou, Konstantinos P. Panousis, Dimitrios Kosmopoulos +2
Automating sign language translation (SLT) is a challenging real world application. Despite its societal importance, though, research progress in the field remains rather poor. Cru…
Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense Attention
Guotai Wang, Shuwei Zhai, Giovanni Lasio +7
Computed Tomography (CT) plays an important role in monitoring radiation-induced Pulmonary Fibrosis (PF), where accurate segmentation of the PF lesions is highly desired for diagno…
Global and Local Interpretation of black-box Machine Learning models to determine prognostic factors from early COVID-19 data
Ananya Jana, Carlos D. Minacapelli, Vinod Rustgi +1
The COVID-19 corona virus has claimed 4.1 million lives, as of July 24, 2021. A variety of machine learning models have been applied to related data to predict important factors su…
Dual Projection Generative Adversarial Networks for Conditional Image Generation
Ligong Han, Martin Renqiang Min, Anastasis Stathopoulos +4
Conditional Generative Adversarial Networks (cGANs) extend the standard unconditional GAN framework to learning joint data-label distributions from samples, and have been establish…