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Special Session 6
Explanatory Knowledge-driven Intelligent Computer Vision and Analysis

Submission Link: http://www.easychair.org/conferences/?conf=icvr2022
(Select Track Special Session 6: Explanatory Knowledge-driven Intelligent Computer Vision and Analysis)

Submission deadline: April 1, 2022
(Final Call!)

Recently, Artificial Intelligence has involved a wide range of scientific fields, the academia and industry have paid widely attention to evolve the core issue of ‘modeling thinking’ processing for the artificial intelligence 2D/3D computer vision and how to use these signals for reasoning. Under the environment of strong understanding of image, voice and text, the real industrial applications need the artificial intelligence processing methods with learning, reasoning and optimizing ability. Gradually, explanatory knowledge discovery has become the basis of the features of the next generation of convergent artificial intelligence, and it is more necessary to express the essence of multiple signals, such as diagrams, rules, functions, even neural networks as well as sub-model features contain multiple layers and distributions.

Artificial intelligence digital signal processing and analysis has played an important role for the intelligent development of the information society. Nowadays, intelligent 2D/3D computer vision based on a wide range of sensors have appeared, such as the intelligent signals of cameras, spectrometers, thermal imaging cameras, hyperspectral imagers, depth cameras, electronic transformers, electric fences, photometric systems, satellite laser ranging systems and radars, etc. Higher requirements of the technologies of the precise digital elevation model analysis, target detection, target recognition, signal diagnosis and prediction of the intelligent signals are needed.

 Related topics:  
The topic is aimed to collect the latest research progress and achievements in the field of intelligent signal processing driven by knowledge. The intelligence signals include but not limited to signals of radar, spectral, infrared, visible light and various sensors, etc.
The range of call papers(including but not limited to):
- Explainable theory of intelligent image processing;
- Preprocessing and analysis of intelligent signal;
- Detection and tracking of intelligent image and 3D point cloud;
- Processing and understanding of computational image;
- Sparse representation and adaptive dictionary;
- Remote sensing data scene classification and target identification;
- Pattern recognition and machine learning;
- Neural network and artificial intelligence;
- Multivariate data fusion processing;
- Processing and application of hyperspectral data;
- Processing and application of spectral signal;
- Processing and analysis of voice signal;
- Signal processing of 3-D augmented reality;

 

 Organizers  
Prof. Hu Zhu, Dr. Guoxia Xu
Email of main Contact person: Prof. Hu Zhu, zhuhu@njupt.edu.cn

Hu Zhu: Hu Zhu received the B.S. degree in mathematics and applied mathematics from Huaibei Coal Industry Teachers College, Huaibei, China, in 2007, and the M.S. and Ph.D. degrees in computational mathematics and pattern recognition and intelligent systems from the Huazhong University of Science and Technology, Wuhan, China, in 2009 and 2013, respectively. In 2013, he joined the Nanjing University of Posts and Telecommunications, Nanjing, China. His research interests include pattern recognition, image processing, and computer vision

Guoxia Xu: Guoxia Xu received the B.S. degree in information and computer science from Yancheng Teachers University, Jiangsu Yancheng, China in 2015, and the M.S. degree in computer science and technology from Hohai University, Nanjing, China in 2018. He is a research fellow in Department of Computer Science, Norwegian University of Science and Technology, Gjovik, Norway. He was a Research Assistant with the City University of Hong Kong, Kowloon Tong, Hong Kong and Chinese University of Hong Kong, Shatin, Hong Kong. His research interests include pattern recognition, image processing, and computer vision.