Abstract:
Surveillance cameras are installed in various locations and contribute to security maintenance and safety. Thus, the video quality of surveillance cameras is important fo...Show MoreMetadata
Abstract:
Surveillance cameras are installed in various locations and contribute to security maintenance and safety. Thus, the video quality of surveillance cameras is important for safety. However, in situations such as nighttime, low-illumination often causes poor image quality. To solve this problem, we propose a system to help acquire quality images of general surveillance cameras utilized in various places through a combination of image quality improvement networks and object detect networks. This will improve safety in low-illumination areas at night. It is also possible to establish a more effective monitoring system for situations occurring in low-illumination areas.
Date of Conference: 02-05 July 2019
Date Added to IEEE Xplore: 22 August 2019
ISBN Information:
ISSN Information:
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- IEEE Keywords
- Index Terms
- Deep Learning ,
- Low Illumination Environments ,
- Image Quality ,
- Nighttime ,
- Improve Image Quality ,
- Surveillance Cameras ,
- Detection Methods ,
- Complex Network ,
- Convolutional Neural Network ,
- Infrared Imaging ,
- Object Detection ,
- Color Images ,
- Blind Spot ,
- Image Enhancement ,
- Edge Computing ,
- Teacher Network ,
- Student Network ,
- Headlights ,
- Accidental Events ,
- Low-rank Approximation ,
- You Only Look Once ,
- Vehicle Detection ,
- Network Pruning ,
- Dimensional Tensor
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Deep Learning ,
- Low Illumination Environments ,
- Image Quality ,
- Nighttime ,
- Improve Image Quality ,
- Surveillance Cameras ,
- Detection Methods ,
- Complex Network ,
- Convolutional Neural Network ,
- Infrared Imaging ,
- Object Detection ,
- Color Images ,
- Blind Spot ,
- Image Enhancement ,
- Edge Computing ,
- Teacher Network ,
- Student Network ,
- Headlights ,
- Accidental Events ,
- Low-rank Approximation ,
- You Only Look Once ,
- Vehicle Detection ,
- Network Pruning ,
- Dimensional Tensor
- Author Keywords