74 citations · 76 across the 4 of their papers we have counts for
6 papers
PGCN: Progressive Graph Convolutional Networks for Spatial-Temporal Traffic Forecasting
Yuyol Shin, Yoonjin Yoon
The complex spatial-temporal correlations in transportation networks make the traffic forecasting problem challenging. Since transportation system inherently possesses graph struct…
A Comparative Study on Basic Elements of Deep Learning Models for Spatial-Temporal Traffic Forecasting
Yuyol Shin, Yoonjin Yoon
Traffic forecasting plays a crucial role in intelligent transportation systems. The spatial-temporal complexities in transportation networks make the problem especially challenging…
Running the COVID-19 marathon: the behavioral adaptations in mobility and facemask over 27 weeks of pandemic in Seoul, South Korea
Jungwoo Cho, Yuyol Shin, Seyun Kim +4
Battle with COVID-19 turned out to be a marathon, not a sprint, and behavioral adjustments have been unavoidable to stay viable. In this paper, we employ a data-centric approach to…
The effect of adaptive mobility policy to the spread of COVID-19 in urban environment: intervention analysis of Seoul, South Korea
Yoonjin Yoon, Soohwan Oh, Jungwoo Cho +4
Although severe mobility restrictions are recognized as the key enabler to contain COVID-19, there has been few scientific studies to validate such approach, especially in urban co…
COVID-19 Mobility Data Collection of Seoul, South Korea
Jungwoo Cho, Soohwan Oh, Seyun Kim +4
The relationship between pandemic and human mobility has received considerable attention from scholars, as it can provide an indication of how mobility patterns change in response…
Incorporating dynamicity of transportation network with multi-weight traffic graph convolutional network for traffic forecasting
Yuyol Shin, Yoonjin Yoon
Traffic forecasting problem remains a challenging task in the intelligent transportation system due to its spatio-temporal complexity. Although temporal dependency has been well st…