Full
Outline
To address the issues of insufficient accuracy and limited speed of the RT-DETR (real-time detection transformer) network in complex scenarios and small object detection, an improved detection algorithm for vehicle images is proposed. This algorithm enhances the ability to capture features of small-scale objects such as vehicles and pedestrians by introducing spatial positional relationship modeling and improves the network's nonlinear modeling performance through a gating mechanism. At the same time, by separating high-frequency and low-frequency detail information and combining feature map segmentation and stitching operations, feature sampling is achieved without information loss. By integrating convolution units (Conv) and batch normalization units (BN) to reduce intermediate processing steps and memory consumption, computational efficiency is increased and model performance is optimized. Experimental results show that compared to the original RT-DETR network, the improved algorithm increases mAP50, mAP50∶95, precision, and recall by 6%, 4.5%, 4.2%, and 4%, respectively. Therefore, optimizing the backbone network structure and strengthening multi-scale feature fusion, focusing on fine-grained information and spatial-frequency domain features, is an effective strategy to improve vehicle detection performance in complex environments.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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