基于MultiResHNet的结构光三维重建技术
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2023/01/01
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Journal
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Indian UGC (journal)
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Refrences21
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杨丽婷 Yang Liting
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刘孝良 Liu Xiaoliang
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储修祥 Chu Xiuxiang
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周路 Zhou Lu
Cite
Yang Liting 杨丽婷, et al. “基于MultiResHNet的结构光三维重建技术”. Laser &Amp; Optoelectronics Progress, vol. 60, no. 20, 2023, p. 2015006, https://doi.org/10.3788/lop223203.
Yang Liting 杨., Liu Xiaoliang 刘., Chu Xiuxiang 储., & Zhou Lu 周. (2023). 基于MultiResHNet的结构光三维重建技术. Laser &Amp; Optoelectronics Progress, 60(20), 2015006. https://doi.org/10.3788/lop223203
Yang Liting 杨, Liu Xiaoliang 刘, Chu Xiuxiang 储, Zhou Lu 周. 基于MultiResHNet的结构光三维重建技术. Laser & Optoelectronics Progress. 2023;60(20):2015006.
Journal Categories
Science
Physics
Optics
Light
Technology
Electrical engineering
Electronics
Nuclear engineering
Electric apparatus and materials
Electric circuits
Electric networks
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| The application of deep-learning technology to fringe projection 3D imaging | 2020 | |||
| Application of deep learning technology to fringe projection 3D imaging | Infrared and Laser Engineering | 2 | 2020 | |
Single-Shot 3D Shape Reconstruction Using Structured Light and Deep Convolutional Neural Networks | Sensors |
| 58 | 2020 |
| Deep neural networks for single- shot structured light profilometry | 2019 | |||
| One-step robust deep learning phase unwrapping | 2019 |
Refrences Analysis
The category
Science: Physics: Optics. Light 8
is the most frequently represented among the references in this article. It primarily includes studies from Sensors and Optics and Lasers in Engineering. The chart below illustrates the number of referenced publications per year.