New Advances in Visual Object Detection and Tracking
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: closed (15 April 2024) | Viewed by 700
Special Issue Editors
Interests: computer vision; machine learning; object detection; object tracking; active learning; semi-supervised learning
Special Issues, Collections and Topics in MDPI journals
2. Former Company Fellow and Capability Leader in Machine Vision, QinetiQ Group PLC/DERA, Malvern WR14 3PS, UK
3. Former Fellow and Current SCR Member, Pembroke College, University of Oxford, Oxford OX3 7LF, UK
Interests: image processing; computer vision; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the realm of computer vision and AI, numerous tasks have taken shape over the years. Notably, visual object detection and tracking (VODT) has emerged as a pivotal area with a multitude of challenges, spurred by the rapid proliferation of its applications across domains such as video surveillance, robotic vision, autonomous vehicles, object-of-interest tracking, indoor navigation, smart airport security, unmanned stores, and more. VODT confronts a spectrum of hurdles including illumination discrepancies, swift object movements, and detection and tracking performance enhancement, as well as the intricate aspects of dealing with occlusions among objects.
Constantly in pursuit of quasi-optimal solutions and heightened accuracy, ODT continually expands its horizons in search of advancements. This dynamic landscape demands both pragmatic technical methodologies and theoretical underpinnings concerning object tracking. Promising pathways that lead to success in this vibrant realm of research are the core focus of our forthcoming Special Issue, dedicated to exploring ODT techniques and their diverse applications.
With great enthusiasm, we invite you to contribute to this endeavor.
Prof. Dr. Phill Kyu Rhee
Dr. Daniel Howard
Guest Editors
Manuscript Submission Information
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Keywords
- visual object detection
- object redetection
- object tracking
- deep learning
- data augmentation
- ensemble methods
- meta learning
- few-shot learning
- zero-shot learning
- incremental learning
- continual learning
- domain adaptation
- domain generalization
- test-time adaptation
- autonomous driving
- robotics
- medical imaging
- defect detection
