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Showing results 1 to 5 of 5

Article
A discrete-time linear model predictive control for motion planning of an autonomous vehicle with adaptive cruise control and obstacle overtaking
  • 2022-08
  • Seo, Ji Hwan. (2022-08). A discrete-time linear model predictive control for motion planning of an autonomous vehicle with adaptive cruise control and obstacle overtaking. Advances in Mechanical Engineering, 14(8). doi: 10.1177/16878132221119899
  • Hindawi Publishing Corporation
  • View : 813
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A Novel Human Detection Scheme and Occlusion Reasoning using LIDAR-RADAR Sensor Fusion

Thesis
A Novel Human Detection Scheme and Occlusion Reasoning using LIDAR-RADAR Sensor Fusion
  • Kwon, Seong Kyung
  • 2017
  • Kwon, Seong Kyung. (2017). A Novel Human Detection Scheme and Occlusion Reasoning using LIDAR-RADAR Sensor Fusion. doi: 10.22677/thesis.2322841
  • DGIST
  • View : 1421
  • Download : 773
Article
Detection scheme for a partially occluded pedestrian based on occluded depth in lidar-radar sensor fusion
  • 2017-11
  • Kwon, Seong Kyung. (2017-11). Detection scheme for a partially occluded pedestrian based on occluded depth in lidar-radar sensor fusion. doi: 10.1117/1.OE.56.11.113112
  • SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
  • View : 1018
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Article
Driving behavior classification and sharing system using cnn-lstm approaches and v2x communication
  • Kwon, Seong Kyung ; 
  • Seo, Ji Hwan ; 
  • Yun, Jun Young ; 
  • Kim, Kyoung-Dae
  • 2021-11
  • Kwon, Seong Kyung. (2021-11). Driving behavior classification and sharing system using cnn-lstm approaches and v2x communication. doi: 10.3390/app112110420
  • MDPI
  • View : 689
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Dynamic All-Red Signal Control Based on Deep Neural Network Considering Red Light Runner Characteristics

Article
Dynamic All-Red Signal Control Based on Deep Neural Network Considering Red Light Runner Characteristics
  • 2020-09
  • Kwon, Seong Kyung. (2020-09). Dynamic All-Red Signal Control Based on Deep Neural Network Considering Red Light Runner Characteristics. doi: 10.3390/app10176050
  • MDPI AG
  • View : 765
  • Download : 287
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