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For the problems of dense targets, severe edge occlusion, and blurred foreground and background that intelligent vehicles face in actual traffic environments, a lightweight object detection algorithm based on image saliency feature fusion is proposed in this paper. Firstly, salient feature maps are extracted based on grayscale images, and input into convolutional neural networks with color images. Secondly, a lightweight fusion network is constructed using the Ghost Model, and the EIoU is used to optimize the model's border localization loss. In order to enhance the detection accuracy of similar occluded targets, nonmaximum suppression algorithm is improved on the backend of the network. Finally, the KITTI dataset is used for training and testing. The experiment shows that the improved detection mAP value of the network reaches 92.7%, with an average accuracy improvement of 3.8% compared to the original network YOLOv5. The accuracy and recall rates are increased by 3% and 6.2%.
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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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