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PRAI 2020 : The 3rd International Conference on Pattern Recognition and Artificial Intelligence

Chengdu, China
Event Date: Aug 28, 2020 - Aug 30, 2020
Submission Deadline: May 20, 2020
Notification of Acceptance: Jun 15, 2020
Camera Ready Version Due : Jun 30, 2020

About

The 3rd International Conference on Pattern Recognition and Artificial Intelligence (PRAI 2020) 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 2020 offers a rich program, including keynote talks, regular papers. We need your contribution and participation to make it a successful event. You can be encouraged by the fact that the excellent presentation will be granted.

Call For Paper

The PRAI 2020 solicits contributions of abstracts, full papers and posters that address themes and topics of the conference. The topics of interest include, but not limited to the following:

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 visiĆ³n
  • 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

IV. Document Analysis, Biometrics and Pattern Recognition Applications

  • Character and Text Recognition
  • Handwriting Recognition
  • Graphics Recognition
  • Document Understanding
  • Gesture and Behavior Analysis
  • Mixed and Augmented Reality
  • Face, fingerprint and iris recognition
  • Other biometrics (gait, soft, speaker, periocular, etc.)
  • Novel biometrics
  • Biometric systems and applications
  • Multi-biometrics
  • Forensic biometrics and applications
  • Bioinformatics
  • Surveillance and Security
  • Search, Retrieval and Visualization
  • Art, Cultural Heritage and Entertainment
  • Industrial image analysis
  • Human computer interaction
  • Analysis of humans
  • Pattern and digital evidence
  • Performance analysis and enhancement
  • Applications of pattern recognition to big data

V. Biomedical Image Analysis and Applications

  • Medical image and signal analysis
  • Biological image and signal analysis
  • Modeling, simulation and visualization
  • Computer-aided detection and diagnosis
  • Image guidance and robot guidance of interventions
  • Content based image retrieval and data mining
  • Medical and biological imaging
  • Segmentation of biomedical images
  • Molecular and cellular image analysis
  • Volumetric image analysis
  • Deformable object tracking and registration
  • Computational anatomy and digital human
  • VR/AR in medical education, diagnosis and surgery
  • Medical robotics
  • Imaging and hardware for health care
  • Brain-computer interfaces
  • Data mining for biological databases
  • Algorithms for molecular biology
  • Deep learning for biomedical image analysis

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