Integrating Deep Learning and Sensor Technologies: Innovations and Applications in Computer Vision
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (15 November 2024) | Viewed by 566
Special Issue Editors
Interests: social computing; human-computer interaction; multimodal and natural language processing; user-centered interaction design
Special Issues, Collections and Topics in MDPI journals
2. Department of Hydraulics and Sanitation, Technology Sector, Federal University of Paraná, Curitiba 81531-990, Brazil
Interests: computer vision; deep learning; Internet of Things (IoT); AI; big data; pattern recognition
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, the integration of deep learning and sensor technologies has emerged as a transformative force in the field of computer vision, driving innovations and applications across a wide range of industries. This fusion not only enhances the capabilities of computer vision systems but also opens up new avenues for research and development. The advent of highly energy-efficient and advanced sensors, coupled with the exponential growth in deep learning algorithms, have significantly expanded the horizons of what can be achieved in computer vision.
This Special Issue, titled "Integrating Deep Learning and Sensor Technologies: Innovations and Applications in Computer Vision", aims to showcase original research and review articles that highlight recent advances, technologies, solutions, applications, and new challenges in this vibrant field. We seek contributions that demonstrate the innovative integration of deep learning and sensor technologies to address complex problems, enhance system performance, and unlock new capabilities in computer vision.
Potential topics for this Special Issue include, but are not limited to, the following:
- Deep learning-enhanced sensor data acquisition for computer vision;
- Algorithmic innovations in sensor data interpretation with deep learning;
- Sensor design innovations for advanced computer vision applications;
- Real-time sensor data processing using deep learning techniques;
- Integrating deep learning and sensors in autonomous systems and smart cities;
- Challenges in deep learning and sensor integration for computer vision;
- Industry and research applications of deep learning in sensor technologies;
- Deep learning for enhanced environmental monitoring with sensor data;
- Novel deep learning approaches for medical diagnostic imaging;
- Deep learning-driven solutions for underwater and aerial sensing technologies.
Dr. Arianna D'Ulizia
Prof. Dr. Heinz Dieter Fill
Dr. Yong Wang
Guest Editors
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Keywords
- deep learning algorithms
- sensor technology integration
- computer vision applications
- real-time data processing
- autonomous systems and smart environments
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