most citedACCL: Adversarial constrained-CNN loss for weakly supervised medical image segmentation

11 citations · 26 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV202111 cited

VersatileGait: A Large-Scale Synthetic Gait Dataset with Fine-GrainedAttributes and Complicated Scenarios

Huanzhang Dou, Wenhu Zhang, Pengyi Zhang +6

With the motivation of practical gait recognition applications, we propose to automatically create a large-scale synthetic gait dataset (called VersatileGait) by a game engine, whi…

cs.CV2020

FcaNet: Frequency Channel Attention Networks

Zequn Qin, Pengyi Zhang, Fei Wu +1

Attention mechanism, especially channel attention, has gained great success in the computer vision field. Many works focus on how to design efficient channel attention mechanisms w…

eess.IV20201 cited

DRR4Covid: Learning Automated COVID-19 Infection Segmentation from Digitally Reconstructed Radiographs

Pengyi Zhang, Yunxin Zhong, Yulin Deng +2

Automated infection measurement and COVID-19 diagnosis based on Chest X-ray (CXR) imaging is important for faster examination. We propose a novel approach, called DRR4Covid, to lea…

eess.IV20203 cited

Learning Diagnosis of COVID-19 from a Single Radiological Image

Pengyi Zhang, Yunxin Zhong, Xiaoying Tang +2

Radiological image is currently adopted as the visual evidence for COVID-19 diagnosis in clinical. Using deep models to realize automated infection measurement and COVID-19 diagnos…

cs.CV202011 cited

ACCL: Adversarial constrained-CNN loss for weakly supervised medical image segmentation

Pengyi Zhang, Yunxin Zhong, Xiaoqiong Li

We propose adversarial constrained-CNN loss, a new paradigm of constrained-CNN loss methods, for weakly supervised medical image segmentation. In the new paradigm, prior knowledge…