activity
20192021
most citedCollaborative City Digital Twin For Covid-19 Pandemic: A Federated Learning Solution

9 citations · 30 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20215 cited

Multimodal Gait Recognition for Neurodegenerative Diseases

Aite Zhao, Jianbo Li, Junyu Dong +5

In recent years, single modality based gait recognition has been extensively explored in the analysis of medical images or other sensory data, and it is recognised that each of the…

cs.CV20219 cited

Associated Spatio-Temporal Capsule Network for Gait Recognition

Aite Zhao, Junyu Dong, Jianbo Li +2

It is a challenging task to identify a person based on her/his gait patterns. State-of-the-art approaches rely on the analysis of temporal or spatial characteristics of gait, and g…

cs.LG20209 cited

Collaborative City Digital Twin For Covid-19 Pandemic: A Federated Learning Solution

Junjie Pang, Jianbo Li, Zhenzhen Xie +2

In this work, we propose a collaborative city digital twin based on FL, a novel paradigm that allowing multiple city DT to share the local strategy and status in a timely manner. I…

cs.CV20203 cited

Search What You Want: Barrier Panelty NAS for Mixed Precision Quantization

Haibao Yu, Qi Han, Jianbo Li +3

Emergent hardwares can support mixed precision CNN models inference that assign different bitwidths for different layers. Learning to find an optimal mixed precision model that can…

q-fin.CP2019

PAGAN: Portfolio Analysis with Generative Adversarial Networks

Giovanni Mariani, Yada Zhu, Jianbo Li +4

Since decades, the data science community tries to propose prediction models of financial time series. Yet, driven by the rapid development of information technology and machine in…

cs.LG20194 cited

RES-PCA: A Scalable Approach to Recovering Low-rank Matrices

Chong Peng, Chenglizhao Chen, Zhao Kang +2

Robust principal component analysis (RPCA) has drawn significant attentions due to its powerful capability in recovering low-rank matrices as well as successful appplications in va…