STrans-YOLOX: Fusing Swin Transformer and YOLOX for Automatic Pavement Crack Detection
Automatic pavement crack detection is crucial for reducing road maintenance costs and ensuring transportation safety. Although convolutional neural networks (CNNs) have been widely used in automatic pavement crack detection, they cannot adequately model the long-range dependencies between pixels and...
Main Authors: | Hui Luo, Jiamin Li, Lianming Cai, Mingquan Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-02-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/3/1999 |
Similar Items
-
Crack Location and Degree Detection Method Based on YOLOX Model
by: Linlin Wang, et al.
Published: (2022-12-01) -
Steel Surface Defect Detection Method Based on Improved YOLOX
by: Chengfei Li, et al.
Published: (2024-01-01) -
CF-YOLOX: An Autonomous Driving Detection Model for Multi-Scale Object Detection
by: Shuiye Wu, et al.
Published: (2023-04-01) -
YOLOX-SwinT algorithm improves the accuracy of AO/OTA classification of intertrochanteric fractures by orthopedic trauma surgeons
by: Xue-Si Liu, et al.
Published: (2025-01-01) -
An Industrial Meter Detection Method Based on Lightweight YOLOX-CAlite
by: Shaokai Wu, et al.
Published: (2023-01-01)