[1] Yang P B, Deng L J, Chen Y et al. Three-dimensional shape measurement of highly reflective objects based on structured light[J]. Chinese Journal of Lasers, 46, 0204004(2019).
[2] Feng W, Tang S J, Zhao X D et al. Three-dimensional shape measurement method of high-reflective surfaces based on adaptive fringe-pattern[J]. Acta Optica Sinica, 40, 0512003(2020).
[3] Feng J Y, Chen H Y, Shi C et al. Three-dimensional measurement of highly-reflective surface using structured light technique[J]. Laser & Optoelectronics Progress, 56, 221202(2019).
[4] Wu S Q, Zhang Y, Zhang S Y et al. Analysis of three-dimensional measurement system and the coordinates calibration in Fourier transform profilometry[J]. Acta Optica Sinica, 29, 2780-2785(2009).
[6] Sun J, Chen W J, Su X Y et al. Study the measurement range of wavelet transform profilometry[J]. Acta Optica Sinica, 27, 647-653(2007).
[7] van der Jeught S, Dirckx J J J. Real-time structured light profilometry: a review[J]. Optics and Lasers in Engineering, 87, 18-31(2016).
[9] Chen C, Yu J, Gao N et al. High accuracy 3D calibration method of phase calculation-based fringe projection system by using LCD screen considering refraction error[J]. Optics and Lasers in Engineering, 126, 105870(2020).
[10] Bai X F, Zhang Z H. 3D shape measurement based on colour fringe projection techniques[J]. Chinese Journal of Scientific Instrument, 38, 1912-1925(2017).
[11] Feng S J, Chen Q, Gu G H et al. Fringe pattern analysis using deep learning[J]. Advanced Photonics, 1, 025001(2019).
[12] Feng S J, Zuo C, Yin W et al. Micro deep learning profilometry for high-speed 3D surface imaging[J]. Optics and Lasers in Engineering, 121, 416-427(2019).
[13] Spoorthi G E, Gorthi S, Gorthi R K S S. PhaseNet: a deep convolutional neural network for two-dimensional phase unwrapping[J]. IEEE Signal Processing Letters, 26, 54-58(2019).
[14] Wang K Q, Li Y, Qian K M et al. One-step robust deep learning phase unwrapping[J]. Optics Express, 27, 15100-15115(2019).
[15] Ronneberger O, Fischer P, Brox T. U-net: convolutional networks for biomedical image segmentation[M]. //Navab N, Hornegger J, Wells W M, et al. Medical image computing and computer-assisted intervention-MICCAI 2015. Lecture notes in computer science, 9351, 234-241(2015).
[20] van der Jeught S, Dirckx J J J. Deep neural networks for single shot structured light profilometry[J]. Optics Express, 27, 17091-17101(2019).
[21] Coelho I M, Coelho V N, Luz E J D S et al. A GPU deep learning metaheuristic based model for time series forecasting[J]. Applied Energy, 201, 412-418(2017).
[22] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C]. //2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA., 770-778(2016).