[1] |
陶芳芳, 宁尚雷, 靳海波. 电阻层析成像技术在气液(固)多相流动体系中的应用进展[J]. 过程工程学报, 2020, 20(4): 371-381.
|
|
Tao Fangfang, Ning Shanglei, Jin Haibo. Application Progress of Electrical Resistance Tomography in Gas-Liquid (Solid) Multiphase Flow Systems[J]. The Chinese Journal of Process Engineering, 2020, 20(4): 371-381.
|
[2] |
陈宇, 夏宗基, 周雨佳. 基于修正稀疏拟牛顿的电容层析成像重建算法[J]. 系统仿真学报, 2019, 31(5): 819-827.
|
|
Chen Yu, Xia Zongji, Zhou Yujia. Electrical Capacitance Tomography Reconstruction Algorithm Based on Modified Sparse Quasi-Newton[J]. Journal of System Simulation, 2019, 31(5): 819-827.
|
[3] |
肖理庆, 王化祥. 基于聚类电阻层析成像静态图像重建算法[J]. 仪器仪表学报, 2016, 37(6): 1258-1266.
|
|
Xiao Liqing, Wang Huaxiang. Static Image Reconstruction Algorithm Based on Clustering Electrical Resistance Tomography[J]. Chinese Journal of Scientific Instrument, 2016, 37(6): 1258-1266.
|
[4] |
De Kerret F, Béguin C, Etienne S. Two-Phase Flow Pattern Identification in a Tube Bundle Based on Void Fraction and Pressure Measurements with Emphasis on Churn Flow[J]. International Journal of Multiphase Flow (S0301-9322), 2017, 94: 94-106.
|
[5] |
李凯锋, 王保良, 黄志尧, 等. K-均值聚类在CCERT系统流型辨识中的应用[J]. 北京航空航天大学学报, 2017, 43(11): 2280-2285.
|
|
Li Kaifeng, Wang Baoliang, Huang Zhiyao, et al. Application of K-means Clustering in Flow Pattern Identification of CCERT System[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(11): 2280-2285.
|
[6] |
吴新杰, 黄国兴, 王静文. 压缩感知在电容层析成像流型辨识中的应用[J]. 光学精密工程, 2013, 21(4): 1062-1068.
|
|
Wu Xinjie, Huang Guoxing, Wang Jingwen. Application of Compressed Sensing in Flow Pattern Identification of Electrical Capacitance Tomography[J]. Optics and Precision Engineering, 2013, 21(4): 1062-1068.
|
[7] |
叶明, 李晓丞, 刘凯, 等. 一种基于U2-Net模型的电阻抗成像方法[J]. 仪器仪表学报, 2021, 42(2): 235-243.
|
|
Ye Ming, Li Xiaocheng, Liu Kai, et al. An Electrical Impedance Imaging Method Based on U2-Net Model[J].Chinese Journal of Scientific Instrument, 2021, 42(2): 235-243.
|
[8] |
Li F, Tan C, Dong F. Electrical Resistance Tomography Image Reconstruction with Densely Connected Convolutional Neural Network[J]. IEEE Transactions on Instrumentation and Measurement (S0018-9456), 2021, 70: 1-11.
|
[9] |
Wu Y, Chen B, Liu K, et al. Shape Reconstruction with Multiphase Conductivity for Electrical Impedance Tomography Using Improved Convolutional Neural Network Method[J]. IEEE Sensors Journal (S1530-437X), 2021, 21(7): 9277-9287.
|
[10] |
Simonyan K, Zisserman A. Very Deep Convolutional Networks for Large-scale Image Recognition[C]//International Conference on Learning Representations.San Diego, CA, USA: ICLR, 2015: 1-14.
|
[11] |
宋蕾, 陈德运, 姚玉梅, 等. Elman神经网络在ECT系统流型辨识中的应用[J]. 哈尔滨理工大学学报, 2014, 19(5): 103-108.
|
|
Song Lei, Chen Deyun, Yao Yumei, et al. Application of Elman Neural Network in ECT System Flow Pattern Identification[J]. Journal of Harbin University of Science and Technology, 2014, 19(5): 103-108.
|
[12] |
李岩, 王璐, 李佳琪. 基于改进ALEXNET卷积神经网络的电容层析成像三维图像重建[J]. 哈尔滨理工大学学报, 2020, 25(4): 109-115.
|
|
Li Yan, Wang Lu, Li Jiaqi. Three-dimensional Image Reconstruction of Electrical Capacitance Tomography Based on Improved ALEXNET Convolutional Neural Network[J]. Journal of Harbin University of Science and Technology, 2020, 25(4): 109-115.
|
[13] |
李峰, 谭超, 董峰. 全连接深度网络的电学层析成像算法[J]. 工程热物理学报, 2019, 40(7): 1526-1531.
|
|
Li Feng, Tan Chao, Dong Feng. Electrical Tomography Algorithm Based on Fully Connected Deep Network[J].Journal of Engineering Thermophysics, 2019, 40(7): 1526-1531.
|
[14] |
肖理庆. 电阻层析成像有限元模型优化与图像重建算法研究[D]. 天津: 天津大学, 2014.
|
|
Xiao Liqing. Research on Finite Element Model Optimization and Image Reconstruction Algorithm of Electrical Resistance Tomography[D]. Tianjin: Tianjin University, 2014.
|
[15] |
张立峰, 王化祥. 一种修正的电阻层析成像Landweber迭代算法[J]. 计量学报, 2016, 37(3): 271-274.
|
|
Zhang Lifeng, Wang Huaxiang. A Modified Landweber Iterative Algorithm for Electrical Resistance Tomography[J]. Acta Metrology Sinica, 2016, 37(3): 271-274.
|
[16] |
徐胜军, 欧阳朴衍, 郭学源, 等. 多尺度特征融合空洞卷积ResNet遥感图像建筑物分割[J]. 光学精密工程, 2020, 28(7): 1588-1599.
|
|
Xu Shengjun, Ouyang Puyan, Guo Xueyuan, et al. Multiscale Feature Fusion Cavity Convolution ResNet Remote Sensing Image Building Segmentation[J]. Optics and Precision Engineering, 2020, 28(7): 1588-1599.
|
[17] |
He K, Zhang X, Ren S, et al. Deep Residual Learning for Image Recognition[C]// IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, NV, USA: IEEE, 2016: 770-778.
|