A Drilling Debris Tracking and Velocity Measurement Method Based on Fine Target Feature Fusion Optimization
During unmanned drilling operations, the velocity of drill cuttings serves as an important indicator of drilling conditions, which necessitates real-time and accurate measurements. To address challenges such as the small size of cuttings, weak feature representations, and complex motion trajectories...
Saved in:
| Main Authors: | Jinteng Yang, Yu Bao, Zumao Xie, Haojie Zhang, Zhongnian Li, Yonggang Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-08-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/15/8662 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Airport-FOD3S: A Three-Stage Detection-Driven Framework for Realistic Foreign Object Debris Synthesis
by: Hanglin Cheng, et al.
Published: (2025-07-01) -
Multi-Object Tracking With Memory Fusion in UAV Videos
by: Yibo Cui, et al.
Published: (2025-01-01) -
Research on Multi-Objective Pedestrian Tracking Algorithm Based on Full-Size Feature Fusion
by: Yihuai Zhu, et al.
Published: (2025-01-01) -
Task Allocation Method for Emergency Active Debris Removal Based on the Fast Elitist Non-Dominated Sorting Genetic Algorithm
by: Hao Lei, et al.
Published: (2025-05-01) -
Learning from Outputs: Improving Multi-Object Tracking Performance by Tracker Fusion
by: Vincenzo M. Scarrica, et al.
Published: (2024-11-01)