3 citations · 4 across the 2 of their papers we have counts for
3 papers
eess.IV2022★ 3 cited
Motion correction in MRI using deep learning and a novel hybrid loss function
Lei Zhang, Xiaoke Wang, Michael Rawson +6
Purpose To develop and evaluate a deep learning-based method (MC-Net) to suppress motion artifacts in brain magnetic resonance imaging (MRI). Methods MC-Net was derived from a UNet…
cs.LG2022★ 1 cited
Neural Network Compression via Effective Filter Analysis and Hierarchical Pruning
Ziqi Zhou, Li Lian, Yilong Yin +1
Network compression is crucial to making the deep networks to be more efficient, faster, and generalizable to low-end hardware. Current network compression methods have two open pr…
cs.CV2021
Adaptive Convolutions with Per-pixel Dynamic Filter Atom
Ze Wang, Zichen Miao, Jun Hu +1
Applying feature dependent network weights have been proved to be effective in many fields. However, in practice, restricted by the enormous size of model parameters and memory foo…