Intelligent Sensors and Computer Vision
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (20 October 2020) | Viewed by 51897
Special Issue Editors
Interests: computer vision; machine learning; optimization
Special Issues, Collections and Topics in MDPI journals
Interests: signal/image/video processing and understanding; color imaging; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: color imaging; image and video processing; analysis and classification; visual information systems; image quality
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The purpose of this Special Issue is to introduce the current developments in Intelligent Sensors and Computer Vision applications exploiting artificial intelligence (AI) techniques.
Intelligent Sensors are devices that may now incorporate different imaging technologies to both detect events in their environment, and to perform logical functions over their own sensings. Visual data can be combined with a wide variety of information ranging from movements (body, head, gait, posture, etc.), physiological data (heart, brain, skin, etc.), and environmental data (audio, location, noise, etc.). Moreover, Intelligent Sensors can be now equipped with more powerful processing resources, thus enabling higher-complexity reasoning based on advanced multimodal, Computer Vision, and AI techniques.
The joint exploitation of vision and other signals within Intelligent Sensors opens the doors to multiple application fields. Based on the domain of action, possible contributions to this Special Issue include, but are not limited to the following:
- Video and multimodal human action recognition
- Video and multimodal anomaly detection for assisted living and surveillance
- Video and multimodal human-computer interaction
- Video and multimodal industrial quality control
- Video and multimodal advanced driver assistant systems (ADAS)
- Deep network architectures for computer vision and multimodal understanding
- Supervised, semi-supervised, and unsupervised learning from video and multimodal signals
- Vision and multimodal understanding applications such as sports, entertainment, healthcare, etc.
- Time series multimodal data analysis
- Deep learning models for multimodal fusion and analysis
- Security and privacy issues for multimodal sensor data
- Modeling, understanding, and leveraging of multimodal signals that can be acquired by intelligent sensors
- Video and multimodal data representation, summarization, and visualization
- Video and multimodal emotion/affect recognition and modeling
Dr. Marco Buzzelli
Prof. Raimondo Schettini
Dr. Joost van de Weijer
Guest Editors
Manuscript Submission Information
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Keywords
- Computer vision
- Intelligent sensors
- Video processing and understanding
- Image processing and understanding
- Multimodal processing and understanding
- Deep learning and machine learning Embedded computer vision
- Human action recognition
- Anomaly detection for assisted living Anomaly detection for video surveillance
- Human–computer interaction
- Industrial quality control Advanced driver assistance systems (ADAS)
- Emotion/affect recognition and modeling
- Supervised, semi-supervised, and unsupervised learning
- Data representation, summarization, and visualization
- Security and privacy issues for multimodal sensor data
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