◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Sheng-Wei Chan

4 papers here

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

author position
  • middle author4

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

fields
  • cs.CV4

identity via Semantic Scholar / OpenAlex

most citedDSNet: An Efficient CNN for Road Scene Segmentation

6 citations · 8 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CV2019★ 2 cited

Multi-Class Lane Semantic Segmentation using Efficient Convolutional Networks

Shao-Yuan Lo, Hsueh-Ming Hang, Sheng-Wei Chan +1

Lane detection plays an important role in a self-driving vehicle. Several studies leverage a semantic segmentation network to extract robust lane features, but few of them can dist…

cs.CV2019★ 6 cited

DSNet: An Efficient CNN for Road Scene Segmentation

Ping-Rong Chen, Hsueh-Ming Hang, Sheng-Wei Chan +1

Road scene understanding is a critical component in an autonomous driving system. Although the deep learning-based road scene segmentation can achieve very high accuracy, its compl…

cs.CV2018

Efficient Road Lane Marking Detection with Deep Learning

Ping-Rong Chen, Shao-Yuan Lo, Hsueh-Ming Hang +2

Lane mark detection is an important element in the road scene analysis for Advanced Driver Assistant System (ADAS). Limited by the onboard computing power, it is still a challenge…

cs.CV2018

Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic Segmentation

Shao-Yuan Lo, Hsueh-Ming Hang, Sheng-Wei Chan +1

Real-time semantic segmentation plays an important role in practical applications such as self-driving and robots. Most semantic segmentation research focuses on improving estimati…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.