Computer Vision and Image Processing in Mobile Devices 2022
1Kookmin University, Seoul, Republic of Korea
2Lakehead University, Lakehead, Canada
3Iloilo Science and Technology University, Iloilo, Philippines
Computer Vision and Image Processing in Mobile Devices 2022
Description
In recent years, artificial intelligence technology represented by deep learning has made breakthroughs in computer vision, natural language processing, speech recognition, and other fields. Due to the wide applications and great potential of computer vision and image processing technology, it has become one of the most popular subfields of artificial intelligence and machine learning.
Mobile devices can be used for information collection and image processing in a variety of environments, which have a wide range of applications. However, due to the limitation of volume and weight, the real-time image processing ability of mobile devices is not strong. In recent years, with the continuous improvement of the computing power of mobile devices and the rapid development of 5G and the Internet of Things technology, more and more studies have been conducted on the efficient operation of computer vision and image processing models on mobile devices. However, there are still many problems in the application of computer vision and image processing technology and these algorithm models in mobile terminals.
The aim of this Special Issue is to cover a wide range of computer vision and image processing applications in mobile devices and the enhancement of related algorithms. Original research and review articles are welcome.
Potential topics include but are not limited to the following:
- Intelligent driving based on image and video analysis
- Applications of small target detection and segmentation in mobile devices
- Multi-modal target detection, recognition, and tracking in mobile devices
- Application of image recognition algorithms in mobile devices
- Moving target image recognition algorithms
- Computer vision algorithms in mobile devices
- Application of image recognition in intelligent business
- Application of deep learning in image processing
- Medical image processing technology
- Deep learning models for visualization
- Interactive AI techniques for visual analytics