Railway Foreign Object Intrusion Detection Using UAV Images and YOLO-UAT
Rapidly detecting foreign objects in the railway’s natural environment is crucial for safe railway operation and passenger safety. Traditional detection methods are limited by technology and environment and are costly and inefficient for large-scale detection. To improve the efficiency of...
Saved in:
Main Authors: | Yang Yang, Zhanhao Liu, Junming Chen, Haiming Gao, Tao Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10851273/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Lightweight YOLO Model for Rice Panicle Detection in Fields Based on UAV Aerial Images
by: Zixuan Song, et al.
Published: (2024-12-01) -
Research on foreign body detection in transmission lines based on a multi-UAV cooperative system and YOLOv7
by: R. Chang, et al.
Published: (2023-10-01) -
YOLO-UP: A High-Throughput Pest Detection Model for Dense Cotton Crops Utilizing UAV-Captured Visible Light Imagery
by: Chenglei Sun, et al.
Published: (2025-01-01) -
MSF-GhostNet: Computationally Efficient YOLO for Detecting Drones in Low-Light Conditions
by: Maham Misbah, et al.
Published: (2025-01-01) -
Nudibranch Suborders Classification based on Densely Connected Convolutional Networks
by: Timothy Christyan, et al.
Published: (2024-03-01)