2022 the 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI 2022) is a forum for presenting excellent results and new challenges facing the field of the reliability and availability of Pattern Recognition and Artificial Intelligence. It brings together experts from industry, governments and academia, experienced in engineering, design and research.
PRAI 2021 proceedings is Indexed by Ei Compendex & Scopus 2 months after the conference
PRAI 2022 offers a rich program, including keynote talks, regular papers.
Important Dates
| Submission Deadline: | March 1, 2022 |
| Notification Date: | April 1, 2022 |
| Registration Deadline: | April 20, 2022 |
| Final Paper Due: | April 20, 2022 |
| Conference Date: | August 19-21, 2022 |
Publication
Accepted papers will be published in PRAI 2022 Conference Proceedings, to be submitted for inclusion into online database and indexed by EI Compendex & Scopus. Selected papers will be recommended to the following SCI journals after extension ( will submit for SCI, Scopus, INSPEC)
Conference Schedule
Day 1, August 19, 2022 Registration,collecting conference materials
Day 2, August 20, 2022 Opening Ceremony & Keynote Speech & Parallel Sessions
Day 3, August 21, 2022 Academic Lab visiting / Local Event
Topics
- Track I. Pattern Recognition and Machine Learning
- Track II. Computer Vision and Robot Vision
- Track III. Image, Speech, Signal and Video Processing
- Track IV. Document Analysis, Biometrics and Pattern Recognition Applications
- Track V. Biomedical Image Analysis and Applications
- Track VI. Artificial Intelligence and Cybersecurity
I. Pattern Recognition and Machine Learning
Statistical, syntactic and structural pattern recognition
Machine learning and data mining
Artificial neural networks
Dimensionality reduction and manifold learning
Classification and clustering
Graphical Models for Pattern Recognition
Representation and analysis in pixel/voxel images
Support vector machines and kernel methods
Symbolic learning
Active and ensemble learning
Deep learning
Pattern recognition for big data
Transfer learning
Semi-supervised learning and spectral methods
Model selection
Reinforcement learning and temporal models
Performance Evaluation
II. Computer Vision and Robot Vision
Vision sensors
Early/low-level vision
Biologically motivated vision
Illumination and reflectance modeling
Image based modeling
Physics-based vision
Perceptual organization
Shape modeling and encoding
Computational photography
3D shape recovery
Motion, tracking and video analysis
3D sensors: depth sensors, ToF, Kinect
2D/3D object detection and recognition
Activity and event analysis
Scene understanding
Occlusion and shadow detection
Stereo and multiple view geometry
Reconstruction and camera motion estimation
Vision for graphics
Deep learning
Vision for robotics
Cognitive and embodied visión
Humanoid vision
III. Image, Speech, Signal and Video Processing
Image, Speech, Signal and Video Processing
Image and video analysis and understanding
Sensor array & multichannel signal processing
Segmentation, features and descriptors
Texture and color analysis
Enhancement, restoration and filtering
Coding, compression and super-resolution
Facial expression recognition
Affective computing
Human computer interaction
Human body motion and gesture based interaction
Audio and acoustic processing and analysis
Automatic speech and speaker recognition
Spoken language processing
Speech and natural language based interaction
Group interaction: analysis of verbal and non-verbal communication
Multimedia analysis, indexing and retrieval
Depth & range sensor data processing and analysis
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