Cross-Scene Multi-Object Tracking for Drones: Leveraging Meta-Learning and Onboard Parameters with the New MIDDTD
Multi-object tracking (MOT) is a key intermediate task in many practical applications and theoretical fields, facing significant challenges due to complex scenarios, particularly in the context of drone-based air-to-ground military operations. During drone flight, factors such as high-altitude envir...
Saved in:
| Main Authors: | Chenghang Wang, Xiaochun Shen, Zhaoxiang Zhang, Chengyang Tao, Yuelei Xu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/9/5/341 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Correction: Wang et al. Cross-Scene Multi-Object Tracking for Drones: Leveraging Meta-Learning and Onboard Parameters with the New MIDDTD. <i>Drones</i> 2025, <i>9</i>, 341
by: Chenghang Wang, et al.
Published: (2025-07-01) -
Object Tracking with the Drone: Systems Analysis
by: Abbas Aqeel Kareem, et al.
Published: (2023-06-01) -
Research on Multi-Objective Pedestrian Tracking Algorithm Based on Full-Size Feature Fusion
by: Yihuai Zhu, et al.
Published: (2025-01-01) -
Re-identification assistance and multi-stage association for pedestrian multi-object tracking
by: Ye Li, et al.
Published: (2025-07-01) -
Tracking algorithm when managing competitive activities of top level teams online based on computer visioncomputer vision
by: A. A. Polozov, et al.
Published: (2024-07-01)