A high-altitude image target detection method based on RT-DETR
By improving the high-altitude image target detection method based on the RT-DETR architecture and utilizing MAFNet, GC3Block, and FGAD modules, the technical problems in the existing technology are solved, the technical challenges of target detection in high-altitude environments are overcome, and the detection performance is improved, especially the detection accuracy and adaptability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-06
- Publication Date
- 2026-07-17
AI Technical Summary
High-altitude image target detection suffers from problems such as insufficient multi-scale feature modeling, weak feature fusion targeting, and easy loss of structural information during upsampling, resulting in limited detection accuracy and poor model adaptability.
An improved RT-DETR architecture is adopted, including the backbone feature extraction network MAFNet, the feature fusion enhancement module GC3Block, and the upsampling enhancement module FGAD. Through multi-scale adaptive fusion, selective fusion, and dynamic upsampling, the feature extraction and fusion capabilities are improved, and the model's adaptability to high-altitude scenes is enhanced.
It improves the accuracy and adaptability of high-altitude image target detection, and enhances detection performance, especially the accuracy of target recognition and localization in complex scenes.
Smart Images
Figure CN122416264A_ABST