Research on User Experience Quality Evaluation Method of Internet of Vehicles Based on sEMG Signal

2021 ◽  
pp. 694-703
Author(s):  
Jiamin Cheng ◽  
Yuan An ◽  
Ping Cui ◽  
Kailiang Zhang
Keyword(s):  
User Experience ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Semg Signal ◽  
Internet Of Vehicles

Objective quality evaluation method of stereo image based on steerable pyramid

2013 ◽  
Vol 32 (3) ◽  
pp. 710-714
Author(s):  
Jin-jin WEI ◽  
Su-mei LI ◽  
Wen-juan LIU ◽  
Yan-jun ZANG
Keyword(s):  
Quality Evaluation ◽  
Evaluation Method ◽  
Stereo Image ◽  
Objective Quality ◽  
Steerable Pyramid

Multi-exposure X-ray image fusion quality evaluation based on CSF and gradient amplitude similarity

2021 ◽  
pp. 1-13
Author(s):  
Yanjie Qi ◽  
Zehui Yang ◽  
Lin Kang
Keyword(s):  
Image Fusion ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Dynamic Range ◽  
Reference Image ◽  
Subjective Perception ◽  
Steel Component ◽  
Imaging Device ◽  
X Ray ◽  
Gradient Amplitude

Due to the limitation of dynamic range of the imaging device, the fixed-voltage X-ray images often produce overexposed or underexposed regions. Some structure information of the composite steel component is lost. This problem can be solved by fusing the multi-exposure X-ray images taken by using different voltages in order to produce images with more detailed structures or information. Due to the lack of research on multi-exposure X-ray image fusion technology, there is no evaluation method specially for multi-exposure X-ray image fusion. For the multi-exposure X-ray fusion images obtained by different fusion algorithms may have problems such as the detail loss and structure disorder. To address these problems, this study proposes a new multi-exposure X-ray image fusion quality evaluation method based on contrast sensitivity function (CSF) and gradient amplitude similarity. First, with the idea of information fusion, multiple reference images are fused into a new reference image. Next, the gradient amplitude similarity between the new reference image and the test image is calculated. Then, the whole evaluation value can be obtained by weighting CSF. In the experiments of MEF Database, the SROCC of the proposed algorithm is about 0.8914, and the PLCC is about 0.9287, which shows that the proposed algorithm is more consistent with subjective perception in MEF Database. Thus, this study demonstrates a new objective evaluation method, which generates the results that are consistent with the subjective feelings of human eyes.

Quantitative image quality evaluation method for UDC (Under Display Camera)

2021 ◽  
Keyword(s):  
Image Quality ◽  
International Symposium ◽  
System Performance ◽  
Quality Evaluation ◽  
Fast Track ◽  
Evaluation Method ◽  
Image Quality Evaluation ◽  
Electronic Imaging ◽  
Quantitative Image

Fast track article for IS&T International Symposium on Electronic Imaging 2021: Image Quality and System Performance XVIII proceedings.

Acceleration data quality assessment for bridge structural health monitoring via statistical and deep-learning approach

2021 ◽  
Author(s):  
Huaqiang Zhong ◽  
Limin Sun ◽  
José Turmo ◽  
Ye Xia
Keyword(s):  
Structural Health Monitoring ◽  
Data Quality ◽  
Health Monitoring ◽  
Structural Damage ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Operating Conditions ◽  
Monitoring Data ◽  
Statistical Characteristics ◽  
Structural Health

<p>In recent years, the safety and comfort problems of bridges are not uncommon, and the operating conditions of in-service bridges have received widespread attention. Many large-span key bridges have installed structural health monitoring systems and collected massive amounts of data. Monitoring data is the basis of structural damage identification and performance evaluation, and it is of great significance to analyze and evaluate its quality. This paper takes the acceleration monitoring data of the main girder and arch rib of a long-span arch bridge as the research object, analyzes and summarizes the statistical characteristics of the data, summarizes 6 abnormal data conditions, and proposes a data quality evaluation method of convolutional neural network. This paper conducts frequency statistics on the acceleration vibration amplitude of the bridge in December 2018 in hours. In order to highlight the end effect of frequency statistics, the whole is amplified and used as network input for training and data quality evaluation. The results are good. It provides another new method for structural monitoring data quality evaluation and abnormal data elimination.</p>

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