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DLAM 2019 : Deep Learning for Activity Monitoring


When Sep 21, 2019 - Sep 21, 2019
Where Taipei (Taiwan)
Submission Deadline Jul 6, 2019
Notification Due Jul 14, 2019
Final Version Due Jul 29, 2019
Categories    deep learning   computer vision   image processing   artificial intelligence

Call For Papers

in conjunction with the 16th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS) 2019

In last decade, Deep Learning has become the most used approach to any computer vision problem; on the other hand, there has been a growing diffusion of many different kinds of the sensing device (static and mobile) for environmental monitoring and surveillance purposes.
The focus of the Workshop is on the application of Deep Learning approaches to activity recognition, with special attention to real applications in real contexts.
We encourage researchers to formulate innovative feature representations, learning methodologies, and end-to-end vision systems based on deep learning. The aim of this workshop is to bring together researchers from different communities (such as Computer Vision, networked embedded sensing, artificial intelligence and so on) which address both the main topics of Deep Learning and Activity Recognition.

Single and multiple object tracking
Human behavior analysis
Deep Learning in embedded systems
Deep Learning for crowd analysis
Individual activity detection and recognition
Multi-agent/multi-sensing activity detection and recognition
Scene understanding
Sensor calibration
Event detection
Real-time applications
Advancements in deep learning

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