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Yongtian Wang

Researcher at Beijing Institute of Technology

Publications -  358
Citations -  4216

Yongtian Wang is an academic researcher from Beijing Institute of Technology. The author has contributed to research in topics: Augmented reality & Holographic display. The author has an hindex of 27, co-authored 357 publications receiving 3010 citations. Previous affiliations of Yongtian Wang include Beijing Film Academy.

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Proceedings ArticleDOI

Kinect based real-time position calibration for nasal endoscopic surgical navigation system

TL;DR: A Kinect based Real-time positional calibration method for nasal endoscopic surgical navigation system that can be retained stably and the potential to expedite the calibration of the tracking system against strong interfering conditions, demonstrating high suitability for a wide range of surgical applications.
Journal ArticleDOI

Phase control in the synthesis of cesium copper iodide compounds for their photoluminescence and radioluminescence study

TL;DR: In this article, the phase control synthesis of CsCu2I3 and Cs3cu2I5 by varying the concentrations of precursor solution is presented. And the UV-pumped light-emitting diodes (UV-LEDs) are realized by adopting Cscu2i3 and cs3Cu2i5 powders as phosphors, showing potential applications for lighting and X-ray detection devices.
Journal ArticleDOI

Freeform beam splitting system design for generating an array of identical sub-beams

TL;DR: In this article, the authors proposed to first convert the input beam into a closely connected Gaussian sub-beam array, which can produce identical discrete spots on the target plane by using the same optical field distribution.
Proceedings ArticleDOI

Effect of radius mismatch on performance of segmented telescopic systems

TL;DR: In this article, a model of segmented systems and an analysis technique are presented to reveal the effect of these errors on the image quality and a new approach is proposed to generate compensators that control the local radius of curvature of each segment efficiently.
Book ChapterDOI

Spatial Probabilistic Distribution Map Based 3D FCN for Visual Pathway Segmentation

TL;DR: This study proposed a novel method based on 3D fully convolutional network (FCN) combined with a spatial probabilistic distribution map (SPDM) for visual pathway segmentation in magnetic resonance imaging that overcame the problem of low contrast and blurry boundary and achieved better segmentation performance.