Coal-rock interface real-time recognition based on the improved YOLO detection and bilateral segmentation network
文献类型：期刊论文
| 作者 | Xu, Shuzhan2; Jiang, Wanming3; Liu, Quansheng2; Wang, Hongsheng3; Zhang, Jun3; Li, Jinlong3; Huang, Xing1; Bo, Yin2,4 |
| 刊名 | UNDERGROUND SPACE
 |
| 出版日期 | 2025-04-01 |
| 卷号 | 21页码:22-43 |
| 关键词 | Coal-rock real-time recognition Grayscale enhancement YOLO Bilateral segmentation network Edge inference |
| ISSN号 | 2096-2754 |
| DOI | 10.1016/j.undsp.2024.07.003 |
| 英文摘要 | To improve the accuracy and efficiency of coal-rock interface recognition, this study proposes a model built on the real-time detection algorithm, you only look once (YOLO), and the lightweight bilateral segmentation network. Simultaneously, the regional similarity transformation function and dragonfly algorithm are introduced to enhance the quality of coal-rock images. The comparison with three other models demonstrates the superior edge inference performance of the proposed model, achieving a mean Average Precision (mAP) of 90.2 at the Intersection over Union (IoU) threshold of 0.50 (mAP50) and 81.4 across a range of IoU thresholds from 0.50 to 0.95 (mAP[50,95]). Furthermore, to maintain high accuracy and real-time recognition capabilities, the proposed model is optimized using the open visual inference and neural network optimization toolkit, resulting in a 144.97% increase in the mean frames per second. Experimental results on four actual coal faces confirm the efficacy of the proposed model, showing a better balance between accuracy and efficiency in coal-rock image recognition, which supports further advancements in coal mining intelligence. |
| 资助项目 | National Natural Science Foundation of China[U21A20153] ; National Natural Science Foundation of China[52074258] ; Key Research and Development Pro-ject of Hubei Province, China[2021BCA133] ; Outstanding Youth Fund Program of the Natural Science Foundation of Hubei Province, China[2022CFA084] ; Wuhan Knowledge Innovation Supporting project[2022010801010162] |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001359065100001 |
| 出版者 | KEAI PUBLISHING LTD |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/43202]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Liu, Quansheng |
| 作者单位 | 1.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China 2.Wuhan Univ, Sch Civil Engn, Wuhan 430072, Peoples R China 3.Shaanxi Nonferrous Yulin Coal Ind Co Ltd, Yulin 719099, Peoples R China 4.Changjiang Inst Survey Planning Design & Res, Wuhan 430010, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xu, Shuzhan,Jiang, Wanming,Liu, Quansheng,et al. Coal-rock interface real-time recognition based on the improved YOLO detection and bilateral segmentation network[J]. UNDERGROUND SPACE,2025,21:22-43. |
| APA | Xu, Shuzhan.,Jiang, Wanming.,Liu, Quansheng.,Wang, Hongsheng.,Zhang, Jun.,...&Bo, Yin.(2025).Coal-rock interface real-time recognition based on the improved YOLO detection and bilateral segmentation network.UNDERGROUND SPACE,21,22-43. |
| MLA | Xu, Shuzhan,et al."Coal-rock interface real-time recognition based on the improved YOLO detection and bilateral segmentation network".UNDERGROUND SPACE 21(2025):22-43. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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