EI-CCVPR 2019 : 2019 2nd International Joint Conference on Computer Vision and Pattern Recognition(CCVPR 2019)
Call For Papers
●2019 2nd International Joint Conference on Computer Vision and Pattern Recognition(CCVPR 2019)-- Ei Compendex & Scopus—Call for papers
｜November 22-24, 2019｜Prague, Czech Republic｜Website: http://www.ccvpr.org/
●Venue:HOLIDAY INN Prague Congress Centre, Prague, Czech Republic
Holiday Inn Prague enjoys a quiet location, a few steps away from Vysehrad Castle and Park. Vysehrad Metro station can be reached within 150 m. All rooms offer air conditioning.
The rooms are equipped with Satellite TV, a minibar and a safe. A choice of pillows and anti-allergic blankets will be provided.
The massage room features oriental decoration and offers a wide selection of massages. There is also a small fitness room.
Modern Czech and international cuisine are served at the Café Restaurant Esprit which features a winter garden and a terrace. A delicacy bistro is also on site.
Historic Wenceslas Square can be reached within 2 stops by metro.
●CCVPR 2019 welcomes researchers, engineers, scientists and industry professionals to an open forum where advances in the field of Computer Vision and Pattern Recognition can be shared and examined. The conference is an ideal platform for keeping up with advances and changes to a consistently morphing field.
●Publication and Indexing
All accepted papers will be published in the digital conference proceedings which will be Indexed by all major citation databases such as Conference Proceedings Citation Index – Science (CPCI-S),(Thomson Reuters, Web of Science), Scopus, Ei Compendex, Inspec, INIS (International Nuclear Information System), Chemical Abstracts, NASA Astrophysics Data System, Polymer Library, etc.
A selection of best papers with extended versions will be recommended to publish in journals.
Prof.Vaclav Skala, University of West Bohemia, Czech Republic
●Program Preview/ Program at a glance
November 22, 2019: Registration + Icebreaker Reception
November 23, 2019: Opening Ceremony+ KN Speech+ Technical Sessions
November 24, 2019: Technical Sessions+ Half day tour/Lab tours
1. PDF version submit via CMT: https://cmt3.research.microsoft.com/CCVPR2019
2. Submit Via email directly to: firstname.lastname@example.org
Ms. Tiya T. Deng
Call for papers(http://www.ccvpr.org/to.html):
(Addresses ow-level processing as well as imaging fundamentals.)
- 3D Imaging
- Enhancement Techniques
- Image Compression, Coding, and Encryption
- Image Data Structures and Databases
- Image Generation, Acquisition, and Processing
- Image Geometry and Multi-view Geometry
- Image Restoration
- Image-based Modeling and Algorithms
- Mathematical Morphology
- Motion and Tracking Algorithms and Applications
- Multimedia Systems and Applications
- Multi-resolution Imaging Techniques
- Novel Image Processing Applications
- Novel Noise Reduction Algorithms
- Performance Analysis and Evaluation
- Segmentation Techniques
- Software Tools for Imaging
- Video Analysis
- Watermarking Methods and Protection + Wavelet Methods
(Addresses mid- to high-level processing as well as vision fundamentals.)
- Active and Robot Vision
- Biometric Authentication
- Camera Networks and Vision
- Cognitive and Biologically Inspired Vision
- Face and Gesture Recognition
- Fuzzy and Neural Techniques in Vision
- Image Feature Extraction
- Machine Learning Technologies for Vision
- Medical Image Processing and Analysis
- Novel Document Image Understanding Techniques
- Novel Vision Application and Case Studies
- Object Recognition
- Sensors and Early Vision
- Soft Computing Methods in Image Processing and Vision
- Special-purpose Machine Architectures for Vision
- Stereo Vision
(Addresses pattern recognition algorithms and methodologies that are of value to the image processing and computer vision research communities.)
- Applications Including: Security, Medicine, Robotic, GIS, Remote Sensing, Industrial Inspection, Nondestructive Evaluation (or NDE), ...
- Bayesian Methods in Pattern Recognition and Matching
- Case studies and Emerging technologies
- Clustering Techniques
- Dimensionality Reduction Methods in Pattern Recognition
- Ensemble Learning Algorithms
- Invariance in Pattern Recognition
- Knowledge-based Recognition
- Parsing Algorithms
- Statistical Pattern Recognition
- Structural and Syntactic Pattern Recognition
- Supervised and Un-supervised Classification Algorithms
- Symbolic Learning