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Yeongmin Ko

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4

identity via Semantic Scholar / OpenAlex

activity
20192022
most citedTask-Driven Deep Image Enhancement Network for Autonomous Driving in Bad Weather

3 citations · 3 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2022

Light Robust Monocular Depth Estimation For Outdoor Environment Via Monochrome And Color Camera Fusion

Hyeonsoo Jang, Yeongmin Ko, Younkwan Lee +1

Depth estimation plays a important role in SLAM, odometry, and autonomous driving. Especially, monocular depth estimation is profitable technology because of its low cost, memory,…

cs.CV2021★ 3 cited

Task-Driven Deep Image Enhancement Network for Autonomous Driving in Bad Weather

Younkwan Lee, Jihyo Jeon, Yeongmin Ko +2

Visual perception in autonomous driving is a crucial part of a vehicle to navigate safely and sustainably in different traffic conditions. However, in bad weather such as heavy rai…

cs.CV2020

Key Points Estimation and Point Instance Segmentation Approach for Lane Detection

Yeongmin Ko, Younkwan Lee, Shoaib Azam +3

Perception techniques for autonomous driving should be adaptive to various environments. In the case of traffic line detection, an essential perception module, many condition shoul…

cs.CV2019

Unconstrained Road Marking Recognition with Generative Adversarial Networks

Younkwan Lee, Juhyun Lee, Yoojin Hong +2

Recent road marking recognition has achieved great success in the past few years along with the rapid development of deep learning. Although considerable advances have been made, t…

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