Gyeungho Choi — accepted AI-conference papers

2024

Lane Segmentation Data Augmentation for Heavy Rain Sensor Blockage Using Realistically Translated Raindrop Images and CARLA Simulator

Jinu Pahk, Seongjeong Park, Jungseok Shim, Sungho Son, Jungki Lee, Jinung An +2

RA-L 2024

Lane segmentation and Lane Keeping Assist System (LKAS) play a vital role in autonomous driving. While deep learning technology has significantly improved the accuracy of lane segmentation, real-world driving scenarios present various challenges. In particular, heavy rainfall not only obscures the r

Cited by 4 Source ↗Scholar ↗

2022

CARLA Simulator-Based Evaluation Framework Development of Lane Detection Accuracy Performance Under Sensor Blockage Caused by Heavy Rain for Autonomous Vehicle

Hyeonjae Jeon, YaeOhn Kim, Minyoung Choi, Donggeon Park, Sungho Son, Jungki Lee +2

RA-L 2022

As self-driving cars have been developed targeting level 4 and 5 autonomous driving, the capability of the vehicle to handle environmental effects has been considered importantly. The sensors installed on autonomous vehicles can be easily affected by blockages (e.g., rain, snow, dust, fog, and other

Cited by 17 Source ↗Scholar ↗