Gate to Computer Vision and Pattern Recognition (gtCVPR)

Gate to Computer Vision and Pattern Recognition (gtCVPR)

ISSN (online): 2408 – 0551

Aims and Scope
Gate to Computer Vision and Pattern Recognition (gtCVPR) is a quarterly published online open access journal aiming to cover the recent advances of computer vision and pattern recognition research fields (CV&PR). Its mission is to promote the research in the theory and applications of CV&PR and to constitute a gate to these areas for both the experienced and early stage researchers.

Topics
Gate to Computer Vision and Pattern Recognition (gtCVPR) journal accepts original and unpublished papers, including but not limited to the following topics:

  • Feature extraction
  • 2D/3D detection, categorization and recognition
  • Scene understanding and reconstruction
  • Shape analysis, representation and matching
  • Visual Sensors
  • Active vision
  • Affective computing
  • Face, gesture and facial expression recognition
  • Biometrics
  • Motion, tracking and video analysis
  • Illumination and reflectance modeling
  • Invariance analysis
  • Action recognition
  • Feature selection
  • Dimensionality reduction
  • Performance evaluation
  • Low level vision
  • Applications of computer vision
  • Stereo vision
  • Classification and clustering
  • Medical image analysis
  • Shading and matting
  • Segmentation and texture
  • Depth analysis and extraction
  • Physics-based vision
  • Cognitive and embodied vision
  • Computational photography
  • Color analysis
  • Deep Learning
  • Active and ensembe learning
  • Human computer interaction
  • Surveillance and security
  • Image and video retrieval, annotation, indexing
  • Datasets construction and analysis
  • Software tools, libraries and toolboxes
  • Applications of pattern recognition

Gate to Computer Vision and Pattern Recognition (gtCVPR)

ISSN (online): 2408 – 0551

Editorial Board

Editor-in-Chief

George A. Papakostas – Eastern Macedonia and Thrace Institute of Technology (EMaTTech), Greece
Contact Information: e-mailwebsiteGoogleScholar

Associate Editors

Jaime Cardoso – University of Porto, Portugal
Contact Information: e-mailwebsiteGoogleScholar

Ankit Chaudhary – Truman State University, USA
Contact Information: e-mailwebsiteGoogleScholar

Khalid M. Hosny – Zagazig University, Egypt
Contact Information: e-mailwebsiteGoogleScholar

Kazuhiro Hotta – Meijo University, Japan
Contact Information: e-mailwebsiteGoogleScholar

Abdul Kadir – Technical University of Malaysia Malacca
Contact Information: e-mailwebsiteGoogleScholar

Li-Jia Li – Yahoo! Research, USA
Contact Information: e-mailwebsiteGoogleScholar

Kui Liu – University of Texas at Dallas, USA
Contact Information: e-mailwebsiteGoogleScholar

Maziar Loghman – Illinois Institute of Technology, USA
Contact Information: e-mailwebsiteGoogleScholar

Cewu Lu – The Hong Kong University of Science and Technology (HKUST)
Contact Information: e-mailwebsiteGoogleScholar

Qiguang Miao – Xidian University,China
Contact Information: e-mailwebsiteGoogleScholar

Bingbing Ni – Advanced Digital Sciences Center (ADSC), Singapore
Contact Information: e-mailwebsiteGoogleScholar

Subrahmanyam Murala – University of Windsor, Canada
Contact Information: e-mailwebsiteGoogleScholar

Nabin Sharma – Griffith University, Queensland, Australia
Contact Information: e-mailwebsiteGoogleScholar

Andrea Torsello – Università Ca’ Foscari Venezia, Italy
Contact Information: e-mailwebsiteGoogleScholar

Carlos M. Travieso – University of Las Palmas de Gran Canaria, Spain
Contact Information: e-mailwebsiteGoogleScholar

Efstratios D. Tsougenis – The Hong Kong University of Science and Technology (HKUST)
Contact Information: e-mailwebsiteGoogleScholar

Rodrigo Verschae – Kyoto University, Japan
Contact Information: e-mailwebsiteGoogleScholar

Bo Yang – Samsung Information Systems America (SISA), USA
Contact Information: e-mailwebsiteGoogleScholar

Haichao Zhang – Duke University, USA
Contact Information: e-mailwebsiteGoogleScholar

Lei Zhen – National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
Contact Information: e-mailwebsiteGoogleScholar

Gate to Computer Vision and Pattern Recognition (gtCVPR)

ISSN (online): 2408 – 0551

Abstracting & Indexing
5-Year Google Impact Factor (2019): 1.500

Gate to Computer Vision and Pattern Recognition (gtCVPR) journal is abstracted and indexed in the following databases:

Gate to Computer Vision and Pattern Recognition (gtCVPR)

ISSN (online): 2408 – 0551

Gate to Computer Vision and Pattern Recognition (gtCVPR)

ISSN (online): 2408 – 0551

Submission

For those researchers who desire to submit their work to the Gate to Computer Vision and Pattern Recognition (gtCVPR) journal the next steps should be followed:

After you have finished the above checks you are ready to submit your work to the gtCVPR journal:

The submission is performed by sending an email with the subject being as “Paper submission: paper title " to the Editorial Office by clicking Submit.

Gate to Computer Vision and Pattern Recognition (gtCVPR)

ISSN (online): 2408 – 0551

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