Region Boosting for Real-Time Object Detection Using Multi-Dimensional Attention
Real-time object detection remains an important topic in computer vision. Balancing the accuracy and speed of object detectors is a formidable challenge for both academic researchers and industry practitioners. In this paper, considering the latest models may be somewhat over-optimized for anchor-fr...
Saved in:
| Main Authors: | Jinlong Chen, Kejian Xu, Yi Ning, Zhi Xu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10745475/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
GFDet: Multi-Level Feature Fusion Network for Caries Detection Using Dental Endoscope Images
by: Nan Gao, et al.
Published: (2024-12-01) -
Enhanced YOLOv10 Framework Featuring DPAM and DALSM for Real-Time Underwater Object Detection
by: Suthir Sriram, et al.
Published: (2025-01-01) -
Shape-Dependent Dynamic Label Assignment for Oriented Remote Sensing Object Detection
by: Xue Zhang, et al.
Published: (2025-01-01) -
A practical object detection-based multiscale attention strategy for person reidentification
by: Bin Zhang, et al.
Published: (2024-12-01) -
A Feature-Enhanced Small Object Detection Algorithm Based on Attention Mechanism
by: Zhe Quan, et al.
Published: (2025-01-01)