Citation: | HE Kai, CHENG Gang, WANG Xi, et al. Research on coal gangue recognition method based on CED-YOLOv5s model[J]. Journal of Mine Automation,2024,50(2):49-56, 82. doi: 10.13272/j.issn.1671-251x.2023090065 |
[1] |
谢和平,任世华,谢亚辰,等. 碳中和目标下煤炭行业发展机遇[J]. 煤炭学报,2021,46(7):2197-2211.
XIE Heping,REN Shihua,XIE Yachen,et al. Development opportunities of the coal industry towards the goal of carbon neutrality[J]. Journal of China Coal Society,2021,46(7):2197-2211.
|
[2] |
王国法,刘峰,孟祥军,等. 煤矿智能化(初级阶段)研究与实践[J]. 煤炭科学技术,2019,47(8):1-36.
WANG Guofa,LIU Feng,MENG Xiangjun,et al. Research and practice on intelligent coal mine construction(primary stage)[J]. Coal Science and Technology,2019,47(8):1-36.
|
[3] |
王国法,刘峰,庞义辉,等. 煤矿智能化——煤炭工业高质量发展的核心技术支撑[J]. 煤炭学报,2019,44(2):349-357.
WANG Guofa,LIU Feng,PANG Yihui,et al. Coal mine intellectualization:the core technology of high quality development[J]. Journal of China Coal Society,2019,44(2):349-357.
|
[4] |
刘峰,曹文君,张建明. 持续推进煤矿智能化 促进我国煤炭工业高质量发展[J]. 中国煤炭,2019,45(12):32-36. doi: 10.3969/j.issn.1006-530X.2019.12.006
LIU Feng,CAO Wenjun,ZHANG Jianming. Continuously promoting the coal mine intellectualization and the high-quality development of China's coal industry[J]. China Coal,2019,45(12):32-36. doi: 10.3969/j.issn.1006-530X.2019.12.006
|
[5] |
王国法,任世华,庞义辉,等. 煤炭工业“十三五”发展成效与“双碳”目标实施路径[J]. 煤炭科学技术,2021,49(9):1-8.
WANG Guofa,REN Shihua,PANG Yihui,et al. Development achievements of China's coal industry during the 13th Five-Year Plan period and future prospects[J]. Coal Science and Technology,2021,49(9):1-8.
|
[6] |
刘峰,曹文君,张建明,等. 我国煤炭工业科技创新进展及“十四五”发展方向[J]. 煤炭学报,2021,46(1):1-15.
LIU Feng,CAO Wenjun,ZHANG Jianming,et al. Current technological innovation and development direction of the 14(th) Five-Year Plan period in China coal industry[J]. Journal of China Coal Society,2021,46(1):1-15.
|
[7] |
PU Yuanyuan,APEL D B,SZMIGIEL A,et al. Image recognition of coal and coal gangue using a convolutional neural network and transfer learning[J]. Energies,2019,12(9). DOI: 10.3390/en12091735.
|
[8] |
雷世威,肖兴美,张明. 基于改进YOLOv3的煤矸识别方法研究[J]. 矿业安全与环保,2021,48(3):50-55.
LEI Shiwei,XIAO Xingmei,ZHANG Ming. Research on coal and gangue identification method based on improved YOLOv3[J]. Mining Safety & Environmental Protection,2021,48(3):50-55.
|
[9] |
徐志强,吕子奇,王卫东,等. 煤矸智能分选的机器视觉识别方法与优化[J]. 煤炭学报,2020,45(6):2207-2216.
XU Zhiqiang,LYU Ziqi,WANG Weidong,et al. Machine vision recognition method and optimization for intelligent separation of coal and gangue[J]. Journal of China Coal Society,2020,45(6):2207-2216.
|
[10] |
郭永存,王希,何磊,等. 基于TW−RN优化CNN的煤矸识别方法研究[J]. 煤炭科学技术,2022,50(1):228-236. doi: 10.3969/j.issn.0253-2336.2022.1.mtkxjs202201023
GUO Yongcun,WANG Xi,HE Lei,et al. Research on coal and gangue recognition method based on TW-RN optimized CNN[J]. Coal Science and Technology,2022,50(1):228-236. doi: 10.3969/j.issn.0253-2336.2022.1.mtkxjs202201023
|
[11] |
李博,王学文,庞尚钟,等. 煤与矸石图像特征分析及试验研究[J]. 煤炭科学技术,2022,50(8):236-246.
LI Bo,WANG Xuewen,PANG Shangzhong,et al. Image characteristics analysis and experimental study of coal and gangue[J]. Coal Science and Technology,2022,50(8):236-246.
|
[12] |
赵明辉. 一种煤矸石优化识别方法[J]. 工矿自动化,2020,46(7):113-116.
ZHAO Minghui. A coal-gangue optimization identification method[J]. Industry and Mine Automation,2020,46(7):113-116.
|
[13] |
沈科,季亮,张袁浩,等. 基于改进YOLOv5s模型的煤矸目标检测[J]. 工矿自动化,2021,47(11):107-111,118.
SHEN Ke,JI Liang,ZHANG Yuanhao,et al. Research on coal and gangue detection algorithm based on improved YOLOv5s model[J]. Industry and Mine Automation,2021,47(11):107-111,118.
|
[14] |
张磊,王浩盛,雷伟强,等. 基于YOLOv5s−SDE的带式输送机煤矸目标检测[J]. 工矿自动化,2023,49(4):106-112.
ZHANG Lei,WANG Haosheng,LEI Weiqiang,et al. Coal gangue target detection of belt conveyor based on YOLOv5s-SDE[J]. Journal of Mine Automation,2023,49(4):106-112.
|
[15] |
LIN T-Y,DOLLAR P,GIRSHICK R B,et al. Feature pyramid networks for object detection[C]. IEEE Conference on Computer Vision and Pattern Recognition,Honolulu,2017:936-944.
|
[16] |
LIU Shu,QI Lu,QIN Haifang,et al. Path aggregation network for instance segmentation[C]. IEEE/CVF Conference on Computer Vision and Pattern Recognition,Salt Lake City,2018:8759-8768.
|
[17] |
HOU Qibin,ZHOU Daquan,FENG Jiashi. Coordinate attention for efficient mobile network design[C]. IEEE/CVF Conference on Computer Vision and Pattern Recognition,Nashville,2021:13708-13717.
|
[18] |
ZHENG Zhaohui,WANG Ping,LIU Wei,et al. Distance-IoU loss:faster and better learning for bounding box regression[EB/OL]. [2023-08-12]. https://arxiv.org/abs/1911.08287v1.
|
[19] |
ZHANG Yifan,REN Weiqiang,ZHANG Zhang,et al. Focal and efficient IOU loss for accurate bounding box regression[J]. Neurocomputing,2022,506:146-157. doi: 10.1016/j.neucom.2022.07.042
|
[20] |
SONG Guanglu,LIU Yu,WANG Xiaogang. Revisiting the sibling head in object detector[EB/OL]. [2023-08-12]. https://arxiv.org/abs/2003.07540.
|
[21] |
WU Yue,CHEN Yinpeng,YUAN Lu,et al. Rethinking classification and localization for object detection[C]. IEEE/CVF Conference on Computer Vision and Pattern Recognition,Seattle,2020:10183-10192.
|
[22] |
GE Zheng,LIU Songtao,WANG Feng,et al. YOLOX:exceeding YOLO series in 2021[EB/OL]. [2023-08-12]. https://arxiv.org/abs/2107.08430.
|