activity
20172021
most citedEmbracing a new era of highly efficient and productive quantum Monte Carlo simulations

7 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20211 cited

Deblurring Processor for Motion-Blurred Faces Based on Generative Adversarial Networks

Shiqing Fan, Ye Luo

Low-quality face image restoration is a popular research direction in today's computer vision field. It can be used as a pre-work for tasks such as face detection and face recognit…

cs.NE20211 cited

Min-Max-Plus Neural Networks

Ye Luo, Shiqing Fan

We present a new model of neural networks called Min-Max-Plus Neural Networks (MMP-NNs) based on operations in tropical arithmetic. In general, an MMP-NN is composed of three types…

cs.CV2021

L-SNet: from Region Localization to Scale Invariant Medical Image Segmentation

Jiahao Xie, Sheng Zhang, Jianwei Lu +1

Coarse-to-fine models and cascade segmentation architectures are widely adopted to solve the problem of large scale variations in medical image segmentation. However, those methods…

eess.IV20201 cited

Cross-Modal Self-Attention Distillation for Prostate Cancer Segmentation

Guokai Zhang, Xiaoang Shen, Ye Luo +5

Automatic segmentation of the prostate cancer from the multi-modal magnetic resonance images is of critical importance for the initial staging and prognosis of patients. However, h…

cs.DC20177 cited

Embracing a new era of highly efficient and productive quantum Monte Carlo simulations

Amrita Mathuriya, Ye Luo, Raymond C. Clay +3

QMCPACK has enabled cutting-edge materials research on supercomputers for over a decade. It scales nearly ideally but has low single-node efficiency due to the physics-based abstra…