PDF
Full
Outline
To address the issues of missed detections, false detections and low accuracy in detecting small and distant objects under adverse conditions such as dust and haze, this paper proposes the EPM-YOLOv8 object detection algorithm. The Efficient Channel Attention (ECA) module is integrated into the C2f module of the YOLOv8n algorithm, enabling the backbone network to focus more effectively on shallow and smaller object features. By adding an additional detection layer and designing a multi-dimension feature fusion architecture, the model’s ability to extract target features and its detection accuracy are significantly improved. Furthermore, a loss function based on the Minimum Point Distance Intersection over Union (MPDIoU) is employed to enhance the precision of bounding box regression. Experimental results demonstrate that the EPM-YOLOv8 model achieves a precision ratio of 83.6% and a detection accuracy of 76.8%, exhibiting superior detection performance under challenging conditions such as haze and dust.
PDF
341
136
| 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 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62199257
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
