High Accuracy Non Ambiguity ToF Lidar System based on Pseudo-Random Noise Code and Phase Detection Method

2019 ◽  
Author(s):  
Yubin Zang ◽  
Hongwei Chen ◽  
Sigang Yang ◽  
Minghua Chen
Keyword(s):  
Detection Method ◽  
Random Noise ◽  
High Accuracy ◽  
Phase Detection ◽  
Lidar System

scholarly journals A Two-Phase Fashion Apparel Detection Method Based on YOLOv4

2021 ◽  
Vol 11 (9) ◽  
pp. 3782
Author(s):  
Chu-Hui Lee ◽  
Chen-Wei Lin
Keyword(s):  
Object Detection ◽  
Transfer Learning ◽  
Detection Method ◽  
Phase Transfer ◽  
Recognition Task ◽  
Phase Detection ◽  
Target Domain ◽  
Two Phase ◽  
Detection Technology ◽  
Fashion Apparel

Object detection is one of the important technologies in the field of computer vision. In the area of fashion apparel, object detection technology has various applications, such as apparel recognition, apparel detection, fashion recommendation, and online search. The recognition task is difficult for a computer because fashion apparel images have different characteristics of clothing appearance and material. Currently, fast and accurate object detection is the most important goal in this field. In this study, we proposed a two-phase fashion apparel detection method named YOLOv4-TPD (YOLOv4 Two-Phase Detection), based on the YOLOv4 algorithm, to address this challenge. The target categories for model detection were divided into the jacket, top, pants, skirt, and bag. According to the definition of inductive transfer learning, the purpose was to transfer the knowledge from the source domain to the target domain that could improve the effect of tasks in the target domain. Therefore, we used the two-phase training method to implement the transfer learning. Finally, the experimental results showed that the mAP of our model was better than the original YOLOv4 model through the two-phase transfer learning. The proposed model has multiple potential applications, such as an automatic labeling system, style retrieval, and similarity detection.

Voltage Phase Difference Detection for Superconductor Quench

2014 ◽  
Vol 933 ◽  
pp. 82-85
Author(s):  
Shi Feng Wang ◽  
Yi Xiang Yue ◽  
Jin Fang
Keyword(s):  
Phase Difference ◽  
Detection Method ◽  
Phase Detection ◽  
Test Results ◽  
Development Platform ◽  
Advantages And Disadvantages ◽  
Difference Detection ◽  
Protection Systems ◽  
Actual Operation ◽  
Voltage Phase

In this paper, the actual operation of the superconducting motor and electrical parameters, a detailed analysis of the advantages and disadvantages of the existing quench detection method. After that I proposed an innovative detection method - voltage phase difference detection. On this basis, the design phase detection method based on the voltage difference quench detection and protection systems, based on stand-alone test and NI development platform test results, we verify its feasibility of the voltage phase difference detection method, and great superiority.

High-Accuracy Ultrasound Contrast Agent Detection Method for Diagnostic Ultrasound Imaging Systems

2015 ◽  
Vol 41 (12) ◽  
pp. 3120-3130 ◽  
Author(s):  
Koichi Ito ◽  
Kazumasa Noro ◽  
Yukari Yanagisawa ◽  
Maya Sakamoto ◽  
Shiro Mori ◽  
...  
Keyword(s):  
Contrast Agent ◽  
Ultrasound Imaging ◽  
Detection Method ◽  
Ultrasound Contrast Agent ◽  
Diagnostic Ultrasound ◽  
High Accuracy ◽  
Imaging Systems ◽  
Ultrasound Contrast

Optimal Data-Driven Modeling-Free Differential-Inversion-Based Iterative Control: A Wafer Stage Example

2020 ◽  
Author(s):  
Zezhou Zhang ◽  
Qingze Zou
Keyword(s):  
System Dynamics ◽  
High Performance ◽  
Random Noise ◽  
High Accuracy ◽  
Data Driven ◽  
Modeling Process ◽  
Random Disturbances ◽  
Noise Disturbances ◽  
Data Driven Modeling ◽  
Iterative Control

Abstract In this paper, an optimal data-driven modeling-free differential-inversion-based iterative control (OMFDIIC) method is proposed for both high performance and robustness in the presence of random disturbances. Achieving high accuracy and fast convergence is challenging as the system dynamics behaviors vary due to the external uncertainties and the system bandwidth is limited. The aim of the proposed method is to compensate for the dynamics effect without modeling process and achieve both high accuracy and robust convergence, by extending the existed modeling-free differential-inversion-based iterative control (MFDIIC) method through a frequency- and iteration-dependent gain. The convergence of the OMFDIIC method is analyzed with random noise/disturbances considered. The developed method is applied to a wafer stage, and shows a significant improvement in the performance.

Orthogonal Phase Detection Method of Light-addressable Potentiometric Sensor

2020 ◽  
Vol 49 (4) ◽  
pp. 423002-423002
Author(s):  
佟星元 Xing-yuan TONG ◽  
闫晓光 Xiao-guang YAN ◽  
陈东 Dong CHEN
Keyword(s):  
Detection Method ◽  
Potentiometric Sensor ◽  
Phase Detection ◽  
Orthogonal Phase ◽  
Light Addressable Potentiometric Sensor
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