Artificial Intelligence-Based Object Detection and Tracking: Theory and Applications
A special issue of AI (ISSN 2673-2688). This special issue belongs to the section "AI Systems: Theory and Applications".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 1494
Special Issue Editors
Interests: computer vision; object tracking; machine learning; self-supervised learning; active learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue explores the symbiotic relationship between artificial intelligence (AI) and object tracking and detection technologies, delving into practical applications and theoretical foundations propelling innovation in computer vision. Object tracking and detection, driven by AI, are pivotal research domains aiming for automatic localization and recognition in images or videos. Applied in surveillance cameras, they enable real-time monitoring, security alerts, and behavior analysis for pedestrians, vehicles, and other objects. In autonomous driving, AI-based tracking and detection contribute to tasks like environment perception, detecting vehicles, pedestrians, and traffic lights. Facial recognition relies on AI-driven object detection and tracking for identity verification in access control and security monitoring. As AI-based object tracking and detection evolve, their applications expand across various domains. The technology’s attention stems from wide-ranging applications, showing progress in recent studies using multi-modal data for tracking and detection tasks. Deep learning algorithms for target tracking exhibit satisfactory performance, overcoming challenges like a shortage of labeled training data and model representation limitations. Current research in AI-based object tracking and detection showcases advancements and ongoing challenges, particularly in diverse application scenarios. The development of these technologies, driven by AI, remains crucial in computer vision. This Special Issue spotlights exceptional research in AI-driven object tracking and detection, emphasizing cutting-edge advances, developments, and emerging trends. We welcome high-quality papers addressing both theoretical and practical dimensions of AI-based object tracking and detection.
Dr. Di Yuan
Dr. Xiu Shu
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. AI is an international peer-reviewed open access monthly 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 1600 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
- artificial intelligence
- computer vision
- object tracking and detection systems
- single/multiple object tracking
- object detection and its applications
- person re-ID and person search
- self-supervised/unsupervised learning
- image fusion and its applications
- thermal infrared target tracking and detection
- tiny/small target tracking and detection
- deep learning for object tracking
- object tracking and its applications
- image restoration
- object recognition
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