New Trends in Computer Vision and Image Processing
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electronic Multimedia".
Deadline for manuscript submissions: 15 December 2024 | Viewed by 107
Special Issue Editors
Interests: geometric modeling; computer animation; computer graphics; image and point cloud-based shape reconstruction; machine learning; applications of ODEs and PDEs in geometric modeling and computer animation
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; computer vision; deep learning; computer graphics
Special Issue Information
Dear Colleagues,
With advancements in artificial intelligence, especially artificial neural networks, many new computer vision and image processing techniques have been developed to improve or transform digital images and analyze and interpret information in image and video data. This Special Issue on "New Trends in Computer Vision and Image Processing" aims to present new advancements and applications in the fields, advance the state of the art in computer vision and image processing, and facilitate the translation of research findings into practical applications. It focuses on leveraging artificial intelligence techniques to enhance visual perception and understanding and addressing challenges and exploring opportunities in various domains such as healthcare, autonomous vehicles, surveillance, and augmented reality. By bringing together contributions from researchers across academia and industry, it seeks to provide a platform for researchers to exchange ideas and showcase innovative approaches in computer vision and image processing and promote the development of novel methodologies and algorithms for solving real-world problems.
This Special Issue entitled “New Trends in Computer Vision and Image Processing” invites original research and comprehensive reviews, including but not limited to the following topics:
- Image classification and recognition;
- Object detection and tracking;
- Image segmentation and feature extraction;
- Artificial intelligence techniques of machine learning for computer animation and image processing;
- 3D vision and reconstruction;
- Image enhancement and restoration techniques;
- Image retrieval;
- Biomedical image processing and analysis;
- Applications of computer vision in robotics and automation;
- Ethical considerations and societal impacts of computer vision technologies.
Prof. Dr. Lihua You
Dr. Shaojun Bian
Dr. Diqiong Jiang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- computer vision
- image processing
- artificial intelligence
- deep learning
- object detection
- image analysis
- 3D vision and reconstruction
