1st International Workshop in Deep Learning for Activity Monitoring (DLAM 2019) Call for Papers

1st International Workshop in Deep Learning for Activity Monitoring (DLAM 2019)

Taipei - TAIWAN, September 21st 2019

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

Workshop Website:  http://dlam2019.isasi.cnr.it/home/

Note: the Workshop will be organized back-to-back with the IEEE
International Conference on Image Processing (ICIP) 2019, which is
also held in Taipei from 9/22 to 9/25. Attendants will be able to
conveniently attend two leading computer vision/image processing
conferences and their workshops in a single trip to Taiwan!



Submission deadline: July 6th 2019
Paper acceptance notification: July 14th 2019
Camera ready: July 29th 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 kind of 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 the
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. 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

- Single and multiple object tracking

- Re-identification

- 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

Note that accepted papers will be published in the Main Conference proceedings.

Please visit our Workshop
website http://dlam2019.isasi.cnr.it/home/
for information about DLAM 2019, while more details about the Main
Conference can be found
at http://avss2019.org/






 Jeff Alstott – IARPA 


Dr. Jeff Alstott is a program manager at IARPA. He previously worked
for MIT, Singapore University of Technology and Design, the World Bank
and the University of Chicago. He obtained his PhD studying complex
networks at the University of Cambridge, and his MBA and bachelor’s
degrees from Indiana University. He has published research in such
areas as animal behavior, computational neuroscience, complex
networks, design science, statistical methods, and S&T forecasting.






Rama Chellappa, University of Maryland, College Park, USA


Pier Luigi Mazzeo, CNR-Institute of Applied Sciences and Intelligent Systems, IT

Paolo Spagnolo, CNR-Institute of Applied Sciences and Intelligent Systems, IT

Lei Zhang,  Microsoft AI & Research, USA





email: wdlam2019@gmail.com

website: http://dlam2019.isasi.cnr.it/home/