Murdoch University, Australia
E-mail: afaq.shah@murdoch.edu.au
Univesity of Regina, Canada
United Arab Emirates University, UAE
Cedars-Sinai Medical Center, LA, USA
There has been a surge of opportunities for the development of deep learning algorithms and platforms for advanced vision systems. This has been boosted by the availability of large amounts of visual data (i.e., big data) and high performance computing systems. These systems will reduce the expensive costs associated with elder's health and home care expenses, and enhance competitiveness in agriculture and marine economies. This workshop aims to gather high quality research papers on state-of-the-art Deep Learning techniques for Video and Image Analysis. We encourage papers on deep learning techniques with all types of contributions including theoretical, engineering and applied.
· Medical Image Analysis
· Generative Adversarial Networks
· Reinforcement Learning
· Image set Classification
· Person detection and identification
· Action recognition
· Gesture recognition
· Deep learning for RGB-D computer vision, e.g., data captured using Kinect scanner
· 3D face detection and recognition using deep learning
· 3D modeling and scene reconstruction
· Image segmentation
· 3D scene understanding
· 3D object detection and tracking,
· 3D object recognition and/or classification
· 3D pose estimation
· Applications of deep learning in computer vision
Paper submission deadline: September 19, 2019
Notification of acceptance: October 2, 2019
Camera Ready: October 10, 2019
Conference Dates: November 18 – 22, 2019
All submissions will be handled electronically.
Authors are requested to directly email their double blind paper to the workshop organiser at afaq.shah@murdoch.edu.au. In the email subject, please mention Deep Learning Workshop Paper - PSIVT 2019.Papers should describe original and unpublished work about the related topics. Each paper will receive double blind reviews, moderated by the workshop chairs. Authors should take into account the following:
- The workshop paper format guidelines are the same as the Main Conference papers
- All papers must be written and presented in English.
- All papers must be submitted in PDF format.