Towards Safer Cities: AI-Powered Infrastructure Fault Detection Based on YOLOv11
The current infrastructure is crucial to metropolitan improvement. Natural factors, aging, and overuse cause these structures to deteriorate, introducing dangers to public well-being. Timely detection of infrastructure failures requires an effective solution. A YOLOv11-based deep learning model has...
Saved in:
| Main Authors: | Raiyen Z. Rakin, Mahmudur Rahman, Kanij F. Borsa, Fahmid Al Farid, Shakila Rahman, Jia Uddin, Hezerul Abdul Karim |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/17/5/187 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
MEIS-YOLO: Improving YOLOv11 for efficient aerial object detection with lightweight design
by: Yicheng Liu, et al.
Published: (2025-06-01) -
Improving Tiny Object Detection in Aerial Images with Yolov5
by: Ahmed Sharba, et al.
Published: (2025-01-01) -
Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8
by: Shafi Muhammad Jiskani, et al.
Published: (2025-01-01) -
Insulator Defect Detection Algorithm Based on Improved YOLOv11n
by: Junmei Zhao, et al.
Published: (2025-02-01) -
Determination of Optimal Dataset Characteristics for Improving YOLO Performance in Agricultural Object Detection
by: Jisu Song, et al.
Published: (2025-03-01)