[1] Liu Y W, Liu M J. Influence of particle size on gas desorption and diffusion difference of soft and hard coal particles[J]. Journal of China Coal Society, 40, 579-587(2015).

[2] Wang S M, Sun Q, Qiao J W et al. Geological guarantee of coal green mining[J]. Journal of China Coal Society, 45, 8-15(2020).

[3] Zhang B B, Mahemuti P. Improved flame target detection algorithm based on YOLOv3[J]. Laser & Optoelectronics Progress, 58, 2411003(2021).

[4] Zhang J Q, Li X Y, Li L Y et al. Landsat 8 remote sensing image based on deep residual fully convolutional network[J]. Laser & Optoelectronics Progress, 57, 102801(2020).

[5] He C E, Xu H J, Wang Z et al. Automatic segmentation algorithm for multimodal magnetic resonance-based brain tumor images[J]. Acta Optica Sinica, 40, 0610001(2020).

[6] Zhang H L, Li Q, Guan X. An improved three-dimensional dual-path brain tumor image segmentation network[J]. Acta Optica Sinica, 41, 0310002(2021).

[7] Xu C, Wang L. Image semantic segmentation method based on improved DeepLabv3+ network[J]. Laser & Optoelectronics Progress, 58, 1610008(2021).

[8] Truong M T N, Kim S. Automatic image thresholding using Otsu’s method and entropy weighting scheme for surface defect detection[J]. Soft Computing, 22, 4197-4203(2018).

[9] Yang Y, Li L W, Jiang W C et al. Multi target detection of high resolution remote sensing image based on optimized Yolo v3 network[J]. Laser & Optoelectronics Progress, 58, 1601002(2021).

[10] Liu X B, Zhang Y W. Ore image segmentation method of conveyor belt based on U-net and Res_UNet models[J]. Journal of Northeastern University (Natural Science), 40, 1623-1629(2019).

[11] Dong K, Jiang D L. Ore image segmentation algorithm based on improved watershed transform[J]. Computer Engineering and Design, 34, 899-903(2013).

[12] Lu C W, Qi F, Ruan S L. Grade determination of fine grain ore based on depth image analysis[J]. Journal of Applied Sciences, 37, 490-500(2019).

[13] Zhou J, Yang F, Shi L Y et al. Ore image segmentation by bipartite graph based on collaborative representation[J]. Computer Engineering, 42, 236-241(2016).

[14] Yuan L, Duan Y Y. A method of ore image segmentation based on deep learning[M]. Huang D S, Gromiha M M, Han K, et al. Intelligent computing methodologies, 10956, 508-519(2018).

[15] Zhang G Y, Liu G Z, Zhu H et al. Ore image thresholding using bi-neighbourhood Otsu’s approach[J]. Electronics Letters, 46, 1666-1668(2010).

[16] Zhang J L, Ye P K, Sun S S. Detection of ore granularity based on morphological image processing[J]. Machinery Design & Manufacture, 68-71(2020).

[17] Malladi S R S P, Ram S, Rodríguez J J. Superpixels using morphology for rock image segmentation[C], 145-148(2014).

[18] Jiao A B, He M, Luo H B. Research on significant edge detection of infrared image based on deep learning[J]. Infrared Technology, 41, 72-77(2019).

[19] Mu G W, Guo Y, Quan X H et al. Magnetic resonance imaging brain tumor image segmentation based on improved U-Net[J]. Laser & Optoelectronics Progress, 58, 0410022(2021).

[20] Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[EB/OL]. https:∥arxiv.org/abs/1409.1556

[21] Dai J F, Qi H Z, Xiong Y W et al. Deformable convolutional networks[C], 764-773(2017).