Difference between revisions of "ICDSC 2019"
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+ | ICDSC 2019 is seeking original high quality submissions addressing innovative research in the broad field of camera networks. Topics include, but are not limited to: | ||
+ | |||
+ | |||
+ | * Distributed smart cameras and network architectures | ||
+ | * Distributed video analytics | ||
+ | * Data aggregation and information fusion | ||
+ | * Smart cameras in Internet of Things (IoT), Industry 4.0 and smart transportation | ||
+ | * Smart image sensors and vision chips | ||
+ | * Mobile vision | ||
+ | * 3D reconstruction | ||
+ | * Autonomous vehicles and autonomous driving | ||
+ | * Social robots | ||
+ | * Body-worn cameras | ||
+ | * Machine learning in distributed camera networks | ||
+ | * Emerging applications (e.g., smart cities, virtual/augmented reality, health monitoring) | ||
+ | * Deep learning on embedded systems |
Latest revision as of 19:57, 1 April 2022
ICDSC 2019 | |
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13th International Conference on Distributed Smart Cameras
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Event in series | ICDSC |
Dates | 2019/09/09 (iCal) - 2019/09/11 |
Homepage: | https://event.unitn.it/icdsc2019/#home |
Location | |
Location: | Trento, Italy |
Important dates | |
Submissions: | 2019/05/24 |
Accepted short papers: | 12 |
Committees | |
General chairs: | Nicola Conci, Caifeng Shan |
PC chairs: | Lucio Marcenaro, Jungong Han |
Table of Contents | |
ICDSC 2019 is seeking original high quality submissions addressing innovative research in the broad field of camera networks. Topics include, but are not limited to:
- Distributed smart cameras and network architectures
- Distributed video analytics
- Data aggregation and information fusion
- Smart cameras in Internet of Things (IoT), Industry 4.0 and smart transportation
- Smart image sensors and vision chips
- Mobile vision
- 3D reconstruction
- Autonomous vehicles and autonomous driving
- Social robots
- Body-worn cameras
- Machine learning in distributed camera networks
- Emerging applications (e.g., smart cities, virtual/augmented reality, health monitoring)
- Deep learning on embedded systems