Call for paper
International Computer Vision conference Original Articles/papers are invited from Industry Persons, Scientist, Academician, Research Scholars, P.G. & U.G. Students for presentation in our International Conference. All articles/papers must be in MS-Word (.doc or .docx) format, including the title, author's name, an affiliation of all authors, e-mail, abstract, keywords, Conclusion, Acknowledgment, and References.
The Candidates with eligibility can click the "Submit Paper/Abstract Now" button and fill up the online submission form and Submit it.
Abstract/Full Paper submission
Final/Full Paper submission is optional: If you don't want your abstract/full paper to be published in the Conference Abstracts & Proceedings CD (with ISBN number) and only want to present it at the conference, it is acceptable.
Page limit: There is a limit of 6-8 pages for a final/full paper. An additional page is chargeable.
Paper language: Final/Full papers should be in English.
All the final papers should be uploaded to the website online system according to "the final paper template" as word doc. or docx since this will be the camera-ready published version. Please note that final papers that are not uploaded to the online System as a word doc./docx after the opening of final paper submissions according to the template above will not be published in the CONFERENCE Abstracts & Proceedings CD (with ISBN number)
All accepted papers will be included in the conference proceedings, which will be published in one of the author's prescribed ScienceFather journals.
Object Detection and Recognition | Image Processing and Enhancement | Computer Vision for Robotics and Autonomous Systems | 3D Computer Vision | Medical Image Analysis | Video Analysis and Understanding | Deep Learning for Computer Vision | Applications of Computer Vision | Human-Computer Interaction and Augmented Reality | Biometrics and Security | Deep Metric Learning | Machine Learning for Computer Vision | Vision and Language | Computational Photography | Generative Models for Computer Vision