Blind Quality Assessment Method to Evaluate Cloud Removal Performance of Aerial Image

2020 ◽  
pp. 280-290
Author(s):  
Zhe Wei ◽  
Yongfeng Liu ◽  
Mengjie Li ◽  
Congli Li ◽  
Song Xue
Keyword(s):  
Quality Assessment ◽  
Assessment Method ◽  
Aerial Image ◽  
Quality Assessment Method ◽  
Cloud Removal

A Video Quality Assessment Method for VoIP Applications Based on User Experience

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Zedong Wang ◽  
Jing Wang ◽  
Fei Wang ◽  
Chengcai Li ◽  
Zesong Fei ◽  
...  
Keyword(s):  
Quality Assessment ◽  
User Experience ◽  
Video Quality ◽  
Assessment Method ◽  
Video Quality Assessment ◽  
Quality Assessment Method

scholarly journals Model Quality Assessment Method Based on Support Vector Machine

2021 ◽  
Vol 25 (1) ◽  
pp. 35-39
Author(s):  
Łukasz Glodek ◽  
Szymon Bysko ◽  
Witold Nocoń
Keyword(s):  
Support Vector Machine ◽  
Quality Assessment ◽  
Industry 4.0 ◽  
Assessment Method ◽  
Support Vector ◽  
Model Quality ◽  
Digital Twin ◽  
Model Quality Assessment ◽  
Virtual Commissioning ◽  
Quality Assessment Method

This paper proposes a model quality assessment method based on Support Vector Machine, which can be used to develop a digital twin. This work is strongly connected with Industry 4.0, in which the main idea is to integrate machines, devices, systems, and IT. One of the goals of Industry 4.0 is to introduce flexible assortment changes. Virtual commissioning can be used to create a simulation model of a plant or conduct training for maintenance engineers. On a branch of virtual commissioning is a digital twin. The digital twin is a virtual representation of a plant or a device. Thanks to the digital twin, different scenarios can be analyzed to make the testing process less complicated and less time-consuming. The goal of this work is to propose a coefficient that will take into account expert knowledge and methods used for model quality assessment (such as Normalized Root Mean Square Error – NRMSE, Maximum Error – ME). NRMSE and ME methods are commonly used for this purpose, but they have not been used simultaneously so far. Each of them takes into consideration another aspect of a model. The coefficient allows deciding whether the model can be used for digital twin appliances. Such an attitude introduces the ability to test models automatically or in a semi-automatic way.

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