Computer Vision and Machine Learning for Intelligent Sensing Systems: Third Edition
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 25 March 2026 | Viewed by 46
Special Issue Editor
Interests: computer vision; machine learning; video analytics; multimedia application
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the rapid development of computer vision and machine learning technology, intelligent sensing systems have been fuelled to make sense of vision sensory data to address complex and challenging real-world sense-making problems. This has brought about tremendous opportunities and challenges in managing and understanding vision sensory data for intelligent sensing systems. With the recent advances in machine learning techniques, we are now able to significantly boost the intelligence of analyzing vision sensory data. This has attracted massive research efforts devoted to addressing challenges in this area, including visual surveillance, smart cities, and healthcare, etc. This Special Issue aims to provide a collection of high-quality research articles that address the broad challenges in both the theoretical and application aspects of computer vision and machine learning for intelligent sensing systems.
The topics of interest include, but are not limited to the following:
- Computer vision for intelligent sensing systems:
- Sensing, representation, and modeling;
- Restoration, enhancement, and super-resolution;
- Color, multispectral, and hyperspectral imaging;
- Stereoscopic, multiview, and 3D processing.
- Machine learning for intelligent sensing systems:
- Classification, detection, and segmentation;
- Action and event recognition, behavior understanding;
- Multimodal machine learning.
- Computer vision applications for healthcare, manufacture, security and safety, biomedical sciences, and other emerging applications.
Dr. Jing Tian
Guest Editor
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Keywords
- machine learning
- deep learning
- computer vision
- image classification
- image analysis
- object detection
- image segmentation
- action recognition
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