Journal of Applied Optics, Volume. 44, Issue 5, 1030(2023)

Classification of combustion state of sintering flame based on CNN-Transformer dual-stream network

Xiuman LIANG, Jinming AN, Xiaohua CAO, Kai ZENG*, Fubin WANG, and Hefei LIU
Author Affiliations
  • College of Electrical Engineering, North China University of Science and Technology, Tangshan 063210, China
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    References(16)

    [1] WANG Fubin, LIU Hefei, HE Jianghong et al. Analysis of sintering operation process parameters and construction of sintering behavior model[J]. Sintering Pellet, 45, 29-34(2020).

    [2] WANG Fubin, LIU Hefei, WANG Rui et al. Multi-core Boosting saliency detection of flame images of sintered sections[J]. Journal of Computer Aided Design and Graphics, 33, 1466-1474(2021).

    [3] LI Jinagyun, YANG Zhifang, ZHENG Junfeng et al. Application of deep learning technology in iron and steel industry[J]. Iron and Steel, 56, 43-49(2021).

    [4] KRIZHEVSKY A, SUTSKEVER I, HINTON G. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90.(2017).

    [5] HE K, ZHANG X, REN S et al. Deep residual learning for image recognition[C](2016).

    [8] ZHANG Qianchuang, GUO Chenxia, YANG Ruifeng et al. Super resolution reconstruction of optical fiber ring image based on lightweight network[J]. Applied Optics, 43, 913-920(2022).

    [14] SZEGEDY C, VANHOUCKE V, IOFFE S et al. Rethinking the inception architecture for computer vision[C], 2818-2826(2016).

    [15] SANDLER M, HOWARD A, ZHU M et al. Mobilenetv2: inverted residuals and linear bottlenecks[C], 4510-4520(2018).

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    Xiuman LIANG, Jinming AN, Xiaohua CAO, Kai ZENG, Fubin WANG, Hefei LIU. Classification of combustion state of sintering flame based on CNN-Transformer dual-stream network[J]. Journal of Applied Optics, 2023, 44(5): 1030

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    Paper Information

    Category: Research Articles

    Received: Sep. 14, 2022

    Accepted: --

    Published Online: Mar. 12, 2024

    The Author Email: Kai ZENG (曾凯)

    DOI:10.5768/JAO202344.0502003

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