activity
20202022
most citedExperiments of Federated Learning for COVID-19 Chest X-ray Images

54 citations · 76 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20222 cited

Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction

Ruixing Zhang, Liangzhe Han, Boyi Liu +2

Recent years have witnessed a rapid growth of applying deep spatiotemporal methods in traffic forecasting. However, the prediction of origin-destination (OD) demands is still a cha…

cs.LG202111 cited

Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges

Zhaohua Zheng, Yize Zhou, Yilong Sun +3

Federated learning plays an important role in the process of smart cities. With the development of big data and artificial intelligence, there is a problem of data privacy protecti…

cs.LG2020

FedCM: A Real-time Contribution Measurement Method for Participants in Federated Learning

Boyi Liu, Bingjie Yan, Yize Zhou +2

Federated Learning (FL) creates an ecosystem for multiple agents to collaborate on building models with data privacy consideration. The method for contribution measurement of each…

eess.IV202054 cited

Experiments of Federated Learning for COVID-19 Chest X-ray Images

Boyi Liu, Bingjie Yan, Yize Zhou +2

AI plays an important role in COVID-19 identification. Computer vision and deep learning techniques can assist in determining COVID-19 infection with Chest X-ray Images. However, f…

physics.soc-ph20209 cited

An Improved Method for the Fitting and Prediction of the Number of COVID-19 Confirmed Cases Based on LSTM

Bingjie Yan, Xiangyan Tang, Boyi Liu +6

New coronavirus disease (COVID-19) has constituted a global pandemic and has spread to most countries and regions in the world. By understanding the development trend of a regional…