Deep Learning Strategy for UAV-Based Multi-Class Damage Detection on Railway Bridges Using U-Net with Different Loss Functions
Periodic visual inspections are currently conducted to maintain the condition of railway bridges. These inspections rely on direct visual assessments by human inspectors, often requiring specialized equipment such as aerial ladders. However, this method is not only time-consuming and costly but also...
Saved in:
| Main Authors: | Yong-Hyoun Na, Doo-Kie Kim |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-08-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/15/8719 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
GhostConv+CA-YOLOv8n: a lightweight network for rice pest detection based on the aggregation of low-level features in real-world complex backgrounds
by: Fei Li, et al.
Published: (2025-08-01) -
DMSA-Net: a deformable multiscale adaptive classroom behavior recognition network
by: Chunyu Dong, et al.
Published: (2025-04-01) -
SRW-YOLO: A Detection Model for Environmental Risk Factors During the Grid Construction Phase
by: Yu Zhao, et al.
Published: (2025-07-01) -
Enhancing medical image segmentation through stacked u-net architectures with interconnected convolution layers
by: Abeer Aljohani
Published: (2025-09-01) -
U-net based approach for pectoralis muscle segmentation in digital mammography
by: Francesca Angelone, et al.
Published: (2025-01-01)