Search Results for author: Xiao Shi

Found 5 papers, 1 papers with code

Deep Cross-species Feature Learning for Animal Face Recognition via Residual Interspecies Equivariant Network

no code implementations ECCV 2020 Xiao Shi, Chenxue Yang, Xue Xia, Xiujuan Chai

We present an animal facial feature fusion module to treat the features of the lower half face as additional information, which improves the proposed RiseNet performance.

Face Alignment Face Recognition

A Machine Learning Approach for Recruitment Prediction in Clinical Trial Design

no code implementations14 Nov 2021 Jingshu Liu, Patricia J Allen, Luke Benz, Daniel Blickstein, Evon Okidi, Xiao Shi

Significant advancements have been made in recent years to optimize patient recruitment for clinical trials, however, improved methods for patient recruitment prediction are needed to support trial site selection and to estimate appropriate enrollment timelines in the trial design stage.

BIG-bench Machine Learning

A Dashboard for Mitigating the COVID-19 Misinfodemic

no code implementations EACL 2021 Zhengyuan Zhu, Kevin Meng, Josue Caraballo, Israa Jaradat, Xiao Shi, Zeyu Zhang, Farahnaz Akrami, Haojin Liao, Fatma Arslan, Damian Jimenez, Mohanmmed Samiul Saeef, Paras Pathak, Chengkai Li

This paper describes the current milestones achieved in our ongoing project that aims to understand the surveillance of, impact of and intervention on COVID-19 misinfodemic on Twitter.

Misinformation

Tripartite Information Mining and Integration for Image Matting

1 code implementation ICCV 2021 Yuhao Liu, Jiake Xie, Xiao Shi, Yu Qiao, Yujie Huang, Yong Tang, Xin Yang

Regarding the nature of image matting, most researches have focused on solutions for transition regions.

Image Matting

Quantum inspired K-means algorithm using matrix product states

no code implementations11 Jun 2020 Xiao Shi, Yun Shang, Chu Guo

Matrix product state has become the algorithm of choice when studying one-dimensional interacting quantum many-body systems, which demonstrates to be able to explore the most relevant portion of the exponentially large quantum Hilbert space and find accurate solutions.

Computational Physics Quantum Physics

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