Lightweight Semantic Segmentation for Road-Surface Damage Recognition Based on Multiscale Learning
With an aging society, the demand for personal mobility for disabled and aging people is increasing. As of 2017, the number of electric wheelchairs in Korea was 90,000 according to the domestic government statistics and has since increased continuously. However, people with disabilities and seniors...
Main Authors: | Seungbo Shim, Gye-Chun Cho |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9103506/ |
Similar Items
-
Lightweight Convolutional Neural Networks with Model-Switching Architecture for Multi-Scenario Road Semantic Segmentation
by: Peng-Wei Lin, et al.
Published: (2021-08-01) -
Semantic Segmentation with Transfer Learning for Off-Road Autonomous Driving
by: Suvash Sharma, et al.
Published: (2019-06-01) -
Implementation of a Lightweight Semantic Segmentation Algorithm in Road Obstacle Detection
by: Bushi Liu, et al.
Published: (2020-12-01) -
Multiscale and Adversarial Learning-Based Semi-Supervised Semantic Segmentation Approach for Crack Detection in Concrete Structures
by: Seungbo Shim, et al.
Published: (2020-01-01) -
LDPNet: A Lightweight Densely Connected Pyramid Network for Real-Time Semantic Segmentation
by: Xuegang Hu, et al.
Published: (2020-01-01)