Keemin Sohn

发表

Separation of car-dependent commuters from normal-choice riders in mode-choice analysis

Keemin Sohn, Jiyoung Yun, Keemin Sohn, 2009 .

Dynamic Origin–Destination Flow Estimation Using Cellular Communication System

Daehyun Kim, Keemin Sohn, Keemin Sohn, 2008, IEEE Transactions on Vehicular Technology.

Space-Based Passing Time Estimation on a Freeway Using Cell Phones as Traffic Probes

Keemin Sohn, Keeyeon Hwang, 2008, IEEE Transactions on Intelligent Transportation Systems.

SENSING SYSTEM AND SENSING METHOD USING MACHINE LEARNING

손기민, Keemin Sohn, Kee-Sun Sohn, 2018 .

An investigation into the station capacities for personal rapid transit systems

Keemin Sohn, 2012 .

An investigation into passenger preference for express trains during peak hours

Keemin Sohn, Junghan Baek, Keemin Sohn, 2016 .

Multi-objective optimization of a road diet network design

Keemin Sohn, Keemin Sohn, 2011 .

Inferring the route-use patterns of metro passengers based only on travel-time data within a Bayesian framework using a reversible-jump Markov chain Monte Carlo (MCMC) simulation

Keemin Sohn, Minseo Lee, Keemin Sohn, 2015 .

An Expectation-Maximization Algorithm to Estimate the Integrated Choice and Latent Variable Model

Keemin Sohn, 2017, Transp. Sci..

Optimizing Train-Stop Positions Along a Platform to Distribute the Passenger Load More Evenly Across Individual Cars

Keemin Sohn, Keemin Sohn, 2013, IEEE Transactions on Intelligent Transportation Systems.

An extremely simple macroscale electronic skin realized by deep machine learning

Namsoo Shin, Min-Young Cho, Keemin Sohn, 2017, Scientific Reports.

Why do passengers choose a specific car of a metro train during the morning peak hours

Keemin Sohn, Hyunmi Kim, Seung Kook Wu, 2014 .

Identifying driver heterogeneity in car-following based on a random coefficient model

Ikki Kim, Taewan Kim, Keemin Sohn, 2013 .

Reinforcement Learning for Joint Control of Traffic Signals in a Transportation Network

Keemin Sohn, Jincheol Lee, Jiyong Chung, 2020, IEEE Transactions on Vehicular Technology.

Factors generating boardings at Metro stations in the Seoul metropolitan area

Keemin Sohn, Hyunjin Shim, Keemin Sohn, 2010 .

Image-Based Learning to Measure the Space Mean Speed on a Stretch of Road without the Need to Tag Images with Labels

Johyun Shin, Seungbin Roh, Keemin Sohn, 2019, Sensors.

CHARACTERIZING URBAN NETWORK PERFORMANCE USING TWO-FLUID MODEL

Chungwon Lee, Keemin Sohn, Jeong Whon Yu, 2005 .

Evaluation of Network Reshuffling Alternatives Based on Key Factors Affecting the Mode Share of Seoul Metro

Ikki Kim, Dae Hyun Kim, Keemin Sohn, 2006 .

Image-Based Learning to Measure Traffic Density Using a Deep Convolutional Neural Network

Keemin Sohn, Jiyong Chung, Jiyong Chung, 2018, IEEE Transactions on Intelligent Transportation Systems.

Image-to-Image Learning to Predict Traffic Speeds by Considering Area-Wide Spatio-Temporal Dependencies

Byeonghyeop Yu, Keemin Sohn, Dohyoung Jo, 2019, IEEE Transactions on Vehicular Technology.

Statistical Model for Forecasting Link Travel Time Variability

Keemin Sohn, Daehyun Kim, 2009 .

Feature Mapping the Seoul Metro Station Areas Based on a Self-Organizing Map

Keemin Sohn, Keemin Sohn, 2013 .

Clustering the seoul metropolitan area by travel patterns based on a deep belief network

Keemin Sohn, Gain Han, Keemin Sohn, 2016, 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC).

Deep-learning architecture to forecast destinations of bus passengers from entry-only smart-card data

Keemin Sohn, Jaeyoung Jung, Jaeyoung Jung, 2017 .

Analyzing the time frame for the transition from leisure-cyclist to commuter-cyclist

Keemin Sohn, Hee Cheol Shin, Hyochul Park, 2011 .

Artificial intelligence for traffic signal control based solely on video images

Keemin Sohn, Jincheol Lee, Hyunjeong Jeon, 2018, J. Intell. Transp. Syst..

Deep-Learning Architectures to Forecast Bus Ridership at the Stop and Stop-To-Stop Levels for Dense and Crowded Bus Networks

Keemin Sohn, Junghan Baek, 2016, Appl. Artif. Intell..

Activity imputation for trip-chains elicited from smart-card data using a continuous hidden Markov model

Keemin Sohn, Gain Han, Keemin Sohn, 2016 .

Non-Anchor-Based Vehicle Detection for Traffic Surveillance Using Bounding Ellipses

Byeonghyeop Yu, Johyun Shin, Gyeongjun Kim, 2020, IEEE Access.

Variational embedding of a hidden Markov model to generate human activity sequences

Keemin Sohn, Jincheol Lee, Seungyun Jeong, 2021 .

Transferability of a Convolutional Neural Network (CNN) to Measure Traffic Density

Gyeongjun Kim, Keemin Sohn, Jiyong Chung, 2021 .

Identifying the Impact on Land Prices of Replacing At-grade or Elevated Railways with Underground Subways in the Seoul Metropolitan Area

Keemin Sohn, Keemin Sohn, Jaewoo Lee, 2014 .

Calibrating a social-force-based pedestrian walking model based on maximum likelihood estimation

Keemin Sohn, Keemin Sohn, Moonsoo Ko, 2013 .

Zonal centrality measures and the neighborhood effect

Keemin Sohn, Keemin Sohn, Daehyun Kim, 2010 .

A systematic decision criterion for the elimination of useless overpasses

Keemin Sohn, Keemin Sohn, 2008 .

Increasing the number of bicycle commuters

Keemin Sohn, Hyochul Park, Keemin Sohn, 2012 .

Commuter dependence on expressways when travelling to work

Keemin Sohn, Daeyeol Chang, 2015 .

Transportation Deficiencies for Older Adults in Seoul, South Korea

Keemin Sohn, Gudmundur F. Ulfarsson, Joon-Ki Kim, 2014 .

An analysis of Metro ridership at the station-to-station level in Seoul

Keemin Sohn, Jinkyung Choi, Keemin Sohn, 2012 .