Real-Time Dynamic Visualization of Wheel Ruts Based on Vega Prime

2013 ◽  
Author(s):  
Wang Xuelong ◽  
Chi Ruijuan ◽  
Zhu Zhongxiang ◽  
Mao Enrong
Keyword(s):  
Real Time ◽  
Dynamic Visualization ◽  
Time Dynamic

Activatable molecular probes for fluorescence-guided surgery, endoscopy and tissue biopsy

2022 ◽  
Author(s):  
Yan Zhang ◽  
Guopeng Zhang ◽  
Ziling Zeng ◽  
Kanyi Pu
Keyword(s):  
Real Time ◽  
Molecular Probes ◽  
Dynamic Visualization ◽  
Optical Signals ◽  
Time Dynamic ◽  
Guided Surgery ◽  
Tissue Biopsy ◽  
Fluorescence Guided Surgery

We highlight the development of activatable molecular probes that trigger the optical signals toward biomarkers, allowing real-time, dynamic visualization of lesions and margins for guided-surgery, endoscopy and tissue biopsy with molecular precision.

Control Model Constructing on Real-Time Dynamic Reversible Lane in Condition of Connected Vehicle

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Lina Mao ◽  
Wenquan Li ◽  
Pengsen Hu ◽  
Guiliang Zhou ◽  
Huiting Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Control Model ◽  
Connected Vehicle ◽  
Time Dynamic

scholarly journals Dynamic Gesture Recognition System with Gesture Spotting Based on Self-Organizing Maps

2021 ◽  
Vol 11 (4) ◽  
pp. 1933
Author(s):  
Hiroomi Hikawa ◽  
Yuta Ichikawa ◽  
Hidetaka Ito ◽  
Yutaka Maeda
Keyword(s):  
Real Time ◽  
Gesture Recognition ◽  
Weight Vector ◽  
Recognition System ◽  
Self Organizing Map ◽  
Self Organizing Maps ◽  
Time Dynamic ◽  
System Input ◽  
Self Organizing ◽  
Gesture Spotting

In this paper, a real-time dynamic hand gesture recognition system with gesture spotting function is proposed. In the proposed system, input video frames are converted to feature vectors, and they are used to form a posture sequence vector that represents the input gesture. Then, gesture identification and gesture spotting are carried out in the self-organizing map (SOM)-Hebb classifier. The gesture spotting function detects the end of the gesture by using the vector distance between the posture sequence vector and the winner neuron’s weight vector. The proposed gesture recognition method was tested by simulation and real-time gesture recognition experiment. Results revealed that the system could recognize nine types of gesture with an accuracy of 96.6%, and it successfully outputted the recognition result at the end of gesture using the spotting result.

Investigation on dynamic holographic display in liquid crystal film doped with carbon dots

2020 ◽  
Vol 10 (6) ◽  
pp. 780-787
Author(s):  
Hongyue Gao ◽  
Suna Li ◽  
Jicheng Liu ◽  
Wen Zhou ◽  
Fan Xu ◽  
...  
Keyword(s):  
Liquid Crystal ◽  
Electric Field ◽  
Real Time ◽  
Diffraction Efficiency ◽  
Carbon Dots ◽  
Applied Electric Field ◽  
Light Polarization ◽  
Forming Process ◽  
Time Dynamic ◽  
Holographic Display

In this paper, we studied the holographic properties of liquid crystal (LC) thin film doped with carbon dots (CDs) which can be used as real-time holographic display screen. The maximum value of diffraction efficiency can reach up to 30% by using a low applied electric field 0.2 V/μm. Holograms in the LC film can be dynamically formed and self-erased. The hologram build-up time and the hologram self-erasure time in the material is fast enough to realize video refresh rate. In addition, the forming process of hologram was studied. The holographic diffraction efficiency was measured depending on the intensity of recording light, applied electric field, the intensity of readout light, and readout light polarization direction. Triple enhancement of the diffraction efficiency value by the modulation of voltage under the condition of low recording energy is presented. Therefore, we develop an easy way to obtain real-time dynamic holographic red, green and blue displays with high diffraction efficiency, which allow the LC film doped with CDs to be used as a holographic 3D display screen.

scholarly journals First Demonstration of Combined kV/MV Image-Guided Real-Time Dynamic Multileaf-Collimator Target Tracking

2009 ◽  
Vol 74 (3) ◽  
pp. 859-867 ◽  
Author(s):  
Byungchul Cho ◽  
Per R. Poulsen ◽  
Alex Sloutsky ◽  
Amit Sawant ◽  
Paul J. Keall
Keyword(s):  
Target Tracking ◽  
Real Time ◽  
Multileaf Collimator ◽  
Time Dynamic ◽  
Image Guided
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