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Yoonjin Yoon
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2020 – today
- 2024
- [j8]Yuyol Shin
, Namwoo Kim
Deep learning framework for vessel trajectory prediction using auxiliary tasks and convolutional networks. Eng. Appl. Artif. Intell. 132: 107936 (2024) - [j7]Yuyol Shin
PGCN: Progressive Graph Convolutional Networks for Spatial-Temporal Traffic Forecasting. IEEE Trans. Intell. Transp. Syst. 25(7): 7633-7644 (2024) - [j6]Daegyu Lee
Design, Field Evaluation, and Traffic Analysis of a Competitive Autonomous Driving Model in a Congested Environment. IEEE Trans. Intell. Transp. Syst. 25(8): 9482-9497 (2024) - 2023
- [j5]Yuyol Shin
Performance Evaluation of Building Blocks of Spatial-Temporal Deep Learning Models for Traffic Forecasting. IEEE Access 11: 136478-136495 (2023) - [c9]Gwanghwan Seong, Namwoo Kim, Seyun Kim, Yoonjin Yoon
Multi-modal Based Region Representation Learning Considering Mobility Data in Seoul. ANT/EDI40 2023: 251-258 - [c8]Hyeyeong Lee, Namwoo Kim, Seyun Kim, Yoonjin Yoon
Detecting socioeconomic changes of Chicago regions between 2013 and 2020 using urban region representation learning. ANT/EDI40 2023: 259-266 - [c7]Namwoo Kim
A Heterogeneous Attention Network Model for Longitudinal Analysis of Socioeconomic and Racial Inequalities in Urban Regions: Evidence from Chicago, IL. SIGSPATIAL/GIS 2023: 100:1-100:4 - [c6]Yuyol Shin
Understanding Urban Economic Status through GNN-based Urban Representation Learning Using Mobility Data. UrbanAI@SIGSPATIAL 2023: 71-80 - 2022
- [j4]Yu Yol Shin, Yoonjin Yoon
Incorporating Dynamicity of Transportation Network With Multi-Weight Traffic Graph Convolutional Network for Traffic Forecasting. IEEE Trans. Intell. Transp. Syst. 23(3): 2082-2092 (2022) - [c5]Soohwan Oh
Risk Analysis of Unmanned Aerial System Operations in Urban Airspace Considering Spatiotemporal Population Dynamics. ITSC 2022: 428-433 - [i8]Yu Yol Shin, Yoonjin Yoon:
PGCN: Progressive Graph Convolutional Networks for Spatial-Temporal Traffic Forecasting. CoRR abs/2202.08982 (2022) - [i7]Namwoo Kim, Yoonjin Yoon:
Effective Urban Region Representation Learning Using Heterogeneous Urban Graph Attention Network (HUGAT). CoRR abs/2202.09021 (2022) - [i6]Daegyu Lee, Hyunki Seong, Seungil Han, Gyuree Kang, David Hyunchul Shim, Yoonjin Yoon
Design, Field Evaluation, and Traffic Analysis of a Competitive Autonomous Driving Model in the a Congested Environment. CoRR abs/2210.17302 (2022) - 2021
- [j3]Kyungeun Lee
Short-Term Traffic Prediction With Deep Neural Networks: A Survey. IEEE Access 9: 54739-54756 (2021) - [c4]Namwoo Kim, Yoonjin Yoon
Regionalization for urban air mobility application with analyses of 3D urban space and geodemography in San Francisco and New York. ANT/EDI40 2021: 388-395 - [c3]Namwoo Kim, Yoonjin Yoon
Representation learning of urban regions via mobility-signature-based zone embedding: a case study of Seoul, South Korea. LocalRec@SIGSPATIAL 2021: 6:1-6:4 - [i5]Yu Yol Shin, Yoonjin Yoon:
A Comparative Study on Basic Elements of Deep Learning Models for Spatial-Temporal Traffic Forecasting. CoRR abs/2111.07513 (2021) - 2020
- [i4]Jungwoo Cho, Soohwan Oh, Seyun Kim, Namwoo Kim, Yu Yol Shin, Haechan Cho, Yoonjin Yoon:
COVID-19 Mobility Data Collection of Seoul, South Korea. CoRR abs/2006.08365 (2020) - [i3]Kyungeun Lee, Moonjung Eo, Euna Jung, Yoonjin Yoon, Wonjong Rhee:
Short-term Traffic Prediction with Deep Neural Networks: A Survey. CoRR abs/2009.00712 (2020) - [i2]Jungwoo Cho, Yu Yol Shin, Seyun Kim, Namwoo Kim, Soohwan Oh, Haechan Cho, Yoonjin Yoon:
Running the COVID-19 marathon: the behavioral adaptations in mobility and facemask over 27 weeks of pandemic in Seoul, South Korea. CoRR abs/2009.09073 (2020)
2010 – 2019
- 2019
- [j2]Sang Eon Lee, Jae-Wook Jung, Youngjun Choi, Yoonjin Yoon
Unmanned Aerial Vehicle Impacts on Heat-Strengthened Glass. IEEE Access 7: 104269-104278 (2019) - [c2]Yuna Noh, Seyun Kim, Yoonjin Yoon
Evaluation on Diversity of Drivers' Cognitive Stress Response using EEG and ECG Signals during Real-Traffic Experiment with an Electric Vehicle. ITSC 2019: 3987-3992 - [i1]Yu Yol Shin, Yoonjin Yoon:
Incorporating Dynamicity of Transportation Network with Multi-Weight Traffic Graph Convolution for Traffic Forecasting. CoRR abs/1909.07105 (2019) - 2018
- [j1]Jeongyun Han
Improving the Energy Saving Process with High-Resolution Data: A Case Study in a University Building. Sensors 18(5): 1606 (2018) - 2015
- [c1]Jungwoo Cho, Yoonjin Yoon
GIS-Based Analysis on Vulnerability of Ambulance Response Coverage to Traffic Condition: A Case Study of Seoul. ITSC 2015: 1402-1407
Coauthor Index
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last updated on 2024-08-23 18:36 CEST by the dblp team
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