Journal of Applied Optics, Volume. 44, Issue 5, 1030(2023)
Classification of combustion state of sintering flame based on CNN-Transformer dual-stream network
[1] Fubin WANG, Hefei LIU, Jianghong HE et al. Analysis of sintering operation process parameters and construction of sintering behavior model. Sintering Pellet, 45, 29-34(2020).
[2] Fubin WANG, Hefei LIU, Rui WANG et al. Multi-core Boosting saliency detection of flame images of sintered sections. Journal of Computer Aided Design and Graphics, 33, 1466-1474(2021).
[3] Jinagyun LI, Zhifang YANG, Junfeng ZHENG et al. Application of deep learning technology in iron and steel industry. Iron and Steel, 56, 43-49(2021).
[4] A KRIZHEVSKY, I SUTSKEVER, G HINTON. ImageNet classification with deep convolutional neural networks. Communications of the ACM, 60, 84-90.(2017).
[5] K HE, X ZHANG, S REN et al. Deep residual learning for image recognition(2016).
[8] Qianchuang ZHANG, Chenxia GUO, Ruifeng YANG et al. Super resolution reconstruction of optical fiber ring image based on lightweight network. Applied Optics, 43, 913-920(2022).
[14] C SZEGEDY, V VANHOUCKE, S IOFFE et al. Rethinking the inception architecture for computer vision, 2818-2826(2016).
[15] M SANDLER, A HOWARD, M ZHU et al. Mobilenetv2: inverted residuals and linear bottlenecks, 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
Category: Research Articles
Received: Sep. 14, 2022
Accepted: --
Published Online: Mar. 12, 2024
The Author Email: ZENG Kai (曾凯)