Development of a network-based power quality diagnosis system

2007 ◽  
Vol 77 (8) ◽  
pp. 1086-1094 ◽  
Author(s):  
Il-Yop Chung ◽  
Dong-Jun Won ◽  
Joong-Moon Kim ◽  
Seon-Ju Ahn ◽  
Seung-Il Moon
2008 ◽  
Vol 78 (3) ◽  
pp. 525
Author(s):  
Il-Yop Chung ◽  
Dong-Jun Won ◽  
Joong-Moon Kim ◽  
Seon-Ju Ahn ◽  
Seung-Il Moon

2019 ◽  
Vol 85 ◽  
pp. 284-294 ◽  
Author(s):  
Diego H.S. Nolasco ◽  
Flavio B. Costa ◽  
Eduardo S. Palmeira ◽  
Denis K. Alves ◽  
Benjamín R.C. Bedregal ◽  
...  

2011 ◽  
Vol 38 (10) ◽  
pp. 12592-12598 ◽  
Author(s):  
M. Faisal ◽  
A. Mohamed ◽  
H. Shareef ◽  
A. Hussain

2003 ◽  
Vol 36 (20) ◽  
pp. 739-743
Author(s):  
Dong-Jun Won ◽  
Il-Yop Chung ◽  
Joong-Moon Kim ◽  
Seon-Ju Ahn ◽  
Seung-Il Moon

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Zhidong Sun ◽  
Jie Sun ◽  
Xueqing Li

The remote video diagnosis system based on the Internet of Things is based on the Internet of Things and integrates advanced intelligent technology. To better promote a harmonious society, constructing a video surveillance system is accelerating in our country. Many enterprises and government agencies have invested much money to build video surveillance systems. The quality of video images is an important index to evaluate the video surveillance system. However, as the number of cameras continues to increase, the monitoring time continues to extend. In the face of many cameras, it is not realistic to rely on human eyes to diagnose video-solely quality. Besides, due to human eyes’ subjectivity, there will be some deviation in diagnosis through human eyes, and these factors bring new challenges to system maintenance. Therefore, relying on artificial intelligence technology and digital image processing technology, the intelligent diagnosis system of monitoring video quality is born using the computer’s efficient mathematical operation ability. Based on artificial intelligence, this paper focuses on studying video quality diagnosis technology and establishes a video quality diagnosis system for video definition detection and noise detection. This article takes the artificial intelligence algorithm in the diagnosis of video quality effect. Compared with the improved algorithm, the improved video quality diagnosis algorithm has excellent improvement and can well finish video quality inspection work. The accuracy of the improved definition evaluation function for the definition detection of surveillance video and noise detection is as high as 95.56%.


2006 ◽  
Vol 1 (1) ◽  
pp. 28-34 ◽  
Author(s):  
Il-Yop Chung ◽  
Dong-Jun Won ◽  
Seon-Ju Ahn ◽  
Joong-Moon Kim ◽  
Seung-Il Moon ◽  
...  

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