ACM--2018 the International Conference on Pattern Recognition and Artificial Intelligence (PRAI 2018)--Ei Compendex and Scopus

2018 the International Conference on Pattern Recognition and Artificial Intelligence (PRAI 2018) (http://www.prai.net/) will be held in Union, NJ, USA at Kean University during August 15-17th, 2018.

â—†Publication:
All accepted papers will be published in International Conference Proceedings Series by ACM, indexed by Ei Compendex and Scopus.
Qualified papers will be recommanded to be published on the International Journal of Machine Learning and Computing (IJMLC, ISSN: 2010-3700), indexed by Ei Inspec and Scopus.

â—†Keynote &Plenary Speakers:
Prof. Chingsong Wei from City University of New York, USA, Prof. Mehmet Celenk from Ohio University, USA and other two excellent professors from USA and other countries will address the keynote speeches.

â—†Submission Method:
Email the submission to [email protected];
Or submit via EasyChair: https://easychair.org/conferences/?conf=prai2018

â—†Contact:
PRAI 2018 Secretary, Mr. Yutao Zhang       
Email: [email protected] 
Tell: +1-206-456-6022 (USA) +86-28-86528465 (China)

â—†CFP: The PRAI 2018 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 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 

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