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To address the high computational and storage demands of object detection algorithms that limit real-time performance of edge devices, this study proposes an improved lightweight road object detection algorithm based on YOLOv7-tiny. First, prior anchor boxes optimized for road object detection are generated using the K-means++ clustering algorithm. Secondly, the backbone network is streamlined by modifying the ELAN structure, while a Lightweight Multi-scale Feature (LMS) module is introduced to optimize the neck network. Finally, the Sigmoid Linear Unit (SiLU) activation function is adopted to accelerate model convergence, and the MPDIoU loss function is employed to further improve detection accuracy. Experimental results demonstrate that the improved model achieves an 18.3% reduction in parameters, a 15.0% decrease in computational complexity, and a 1.1% increase in mean average precision across all categories. When deployed on Jetson TX2 with TensorRT acceleration, the detection speed reaches 48 frames per second, essentially meeting real-time requirements for road object detection applications.
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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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