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Huachun Wang
at Beijing Univ of Posts and Telecommunications
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Publications (6)
Proceedings Article | 27 March 2022 Paper
An intelligent generating method for multi-target attacking strategy based on environment-aware deep reinforcement learning
Proceedings Volume 12169, 121695O (2022) https://doi.org/10.1117/12.2624431
KEYWORDS: Strategic intelligence, Detection and tracking algorithms, Neural networks, Motion models, Environmental sensing, Target detection, Performance modeling, Cognitive modeling
SPIE Journal Paper | 6 December 2021
Automatic parameters measurement of lenticular-lens array for autostereoscopic three-dimensional display based on deep reinforcement learning
Xiao Guo, Xinzhu Sang, Duo Chen, Peng Wang, Huachun Wang, Binbin Yan
OE, Vol. 60, Issue 12, 123103, (December 2021) https://doi.org/10.1117/12.10.1117/1.OE.60.12.123103
KEYWORDS: 3D displays, 3D image processing, 3D metrology, Cameras, Optical engineering, Image processing, Time metrology, Image quality, Iterative methods, Convolutional neural networks
SPIE Journal Paper | 26 May 2021
Depth reconstruction for 3D light-field display based on axially distributed light field
Tong Yao, Xinzhu Sang, Peng Wang, Songlin Xie, Duo Chen, Huachun Wang
OE, Vol. 60, Issue 05, 053103, (May 2021) https://doi.org/10.1117/12.10.1117/1.OE.60.5.053103
KEYWORDS: 3D displays, 3D image processing, 3D image reconstruction, Advanced distributed simulations, Cameras, Optical engineering, Image segmentation, Volume rendering, LCDs, Geometrical optics
Proceedings Article | 18 November 2019 Paper
High-resolution 3D model reconstruction for light field display
Proceedings Volume 11188, 111881S (2019) https://doi.org/10.1117/12.2537261
KEYWORDS: 3D modeling, 3D displays, Reconstruction algorithms, Optical flow, New and emerging technologies, Evolutionary algorithms, Neural networks, Cameras, 3D image processing, Image segmentation
Proceedings Article | 2 November 2018 Paper
An optical flow network for enhancing the edge information
Proceedings Volume 10817, 108170T (2018) https://doi.org/10.1117/12.2500540
KEYWORDS: Optical flow, Convolution, Neural networks, Motion estimation, Optical networks, Detection and tracking algorithms, Machine vision, Computer vision technology
Showing 5 of 6 publications
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