International Journal of Computational Vision and Robotics
- Editor in Chief
- Prof. Srikanta Patnaik
- ISSN online
- ISSN print
- 6 issues per year
- CiteScore 2020 1.1
IJCVR is an international refereed journal in the field of image processing, pattern recognition, machine vision and image understanding, providing an international forum for professionals, engineers and researchers.
Topics covered include
- Early vision, vision systems
- Computer vision, AI applications
- Computer games and animation
- Computational geometry
- Shape/range/motion analysis
- Signal/image processing
- Image matching, medical imaging
- Pattern/face recognition
- Architecture, languages
- Parallel computer vision
- Interactive computational models
- Biological vision, alternative eyes
- 3D vision/perception
- Robotics, multi-sensory data fusion
IJCVR aims to provide an international forum for all scientists and engineers engaged in research and development activities in the field of machine vision, robotics, cognition and perception. IJCVR publishes various articles comprising of innovations, comparisons, extensions and new applications.
IJCVR offers a forum to help academics, researchers, R&D personnel, consultants and manufacturers in the field of computer vision, robotics and intelligent systems to disseminate information and to learn from each other's work.
IJCVR reports various intelligent and soft computing techniques in the areas of image processing and pattern recognition. This also encourages the researchers to integrate various techniques of computer vision with robotics, image understanding and cognitive science. Special Issues devoted to important topics in the areas image processing, pattern recognition, machine vision and image understanding will also be published periodically.
IJCVR is indexed in:
- Scopus (Elsevier)
- Compendex [formerly Ei] (Elsevier)
- Academic OneFile (Gale)
- ACM Digital Library
- cnpLINKer (CNPIEC)
- DBLP Computer Science Bibliography
- Expanded Academic ASAP (Gale)
- Google Scholar
- Info Trac (Gale)
- ProQuest Advanced Technologies Database with Aerospace
IJCVR is listed in:More journal lists/directories...
Editor in Chief
- Patnaik, Srikanta, SOA University and Interscience Institute of Management and Technology, Bhubaneswar, India
- Jia, Jiancheng (Kevin), International Game Technology, USA
- Shi, Junsheng, Yunnan Normal University, China
Editorial Board Members
- Bendjenna, Hakim, University of Larbi Tebessi, Algeria
- Bhatia, Sanjiv K., University of Missouri - St. Louis, USA
- Chaudhuri, Debasis, Defence Electronics Applications Laboratory, India
- Damper, R.I., University of Southampton, UK
- DeSouza, Guilherme N., University of Western Australia, Australia
- Gini, Maria, University of Minnesota, USA
- Governi, Lapo, University of Florence, Italy
- Han, Wang, Nanyang Technological University, Singapore
- Koshizen, Takamasa, Honda Research Institute Japan Co. Ltd., Japan
- Kothari, Ravi, IBM Research - India, India
- Kountchev, Roumen Kirilov, Technical University of Sofia, Bulgaria
- Krim, Hamid, North Carolina State University, USA
- Lee, Chan-Su, Yeungnam University, South Korea
- Lima, Pedro U., Instituto Superior Técnico, Puerto Rico
- Mata, Mario, Universidad Europea de Madrid, Spain
- Michalewicz, Zbigniew, University of Adelaide, Australia
- Moreno, Luis, University of Carlos III, Spain
- Nahvi, Ali, K.N. Toosi University of Technology, Iran
- Ranjan, Jayanthi, Institute of Management Technology (IMT), India
- Ruichek, Yassine, University of Technology of Belfort-Montbéliard, France
- Samal, Ashok, University of Nebraska-Lincoln, USA
- Sethi, Ishwar, Oakland University, USA
- Shafazand, M. Hassan, Shahid Bahonar University of Kerman, Iran
- Sharma, Rajeev, Pennsylvania State University, USA
- Sun, Yu, Michigan State University, USA
- Tan, Kok Kiong, National University of Singapore, Singapore
- Wren, Christopher R., Mitsubishi Electric Research Laboratories, USA
- Yang, Yeon-Mo, Kumoh National Institute of Technology, South Korea
- Yeasin, Mohammed, University of Memphis, USA
- Yezzi, Anthony, Georgia Institute of Technology, USA
- Yin, Peng-Yeng, National Chi Nan University, Taiwan
A few essentials for publishing in this journal
- Submitted articles should not have been previously published or be currently under consideration for publication elsewhere.
- Conference papers may only be submitted if the paper has been completely re-written (more details available here) and the author has cleared any necessary permissions with the copyright owner if it has been previously copyrighted.
- Briefs and research notes are not published in this journal.
- All our articles go through a double-blind review process.
- All authors must declare they have read and agreed to the content of the submitted article. A full statement of our Ethical Guidelines for Authors (PDF) is available.
- There are no charges for publishing with Inderscience, unless you require your article to be Open Access (OA). You can find more information on OA here.
- All articles for this journal must be submitted using our online submissions system.
- View Author guidelines.
Up-converting for Super SloMo video
21 September, 2021
Research published in the International Journal of Computational Vision and Robotics, points to several approaches that might be used to up-convert Super SloMo video files with deep learning offering improvements in final quality. The methods described offer a way to convert a video with a lower number of frames per second to be converted to one with a higher number of frames per second. Minseop Kim and Haechul Choi of the Hanbat National University in Daejeon, Republic of Korea explain how a training data set can be used to gain optimal results with Super SloMo boosting signal-to-noise ratio significantly [...]More details...
5 August, 2021
There are many reasons why someone might wish to know the precise camera that was used to take a digital photo – whether for criminal or fraud investigation, copyright and provenance, and perhaps even for archival purposes. Work published in the International Journal of Computational Vision and Robotics, provides a novel feature-based approach for such an identification using photo-response non-uniformity (PRNU) noise. Megha Borole and Satish Kolhe of the School of Computer Sciences at Kavayitri Bahinabai Chaudhari North Maharashtra University in Jalgaon, Maharashtra, India, explain how the pattern of noise in a digital image can act as a "fingerprint" unique to a particular camera [...]More details...