Deep Learning Workshop

International Workshop on Deep Learning for Video and Image Analysis

in conjunction with PSIVT 2019

Sydney, Australia


  • Syed Afaq Shah

Murdoch University, Australia


  • Abdul Bais

Univesity of Regina, Canada

  • Fady Al-Najjar,

United Arab Emirates University, UAE

  • Touseef Ahmed Qureshi

Cedars-Sinai Medical Center, LA, USA

Program Committee

  • Debiao Li, UCLA, USA
  • Sofiane Yous, Intel Corporation, Ireland
  • Usman Qayyum, NESCOM, Pakistan
  • Hossein Rahmani, Lancaster University, UK
  • Hasan Firdaus, IIU, Malaysia
  • Syed Zulqarnain Gilani, ECU, Australia
  • Naveed Mufti, UET Mardan, Pakistan
  • Muhammad Farooq, Phyn, USA
  • Muhammad Asif Manzoor, University of Regina, Canada
  • Munkhjargal Gochoo, UAE University, UAE
  • Tariq Bashir, COMSATS University Islamabad, Pakistan
  • Muhammad Sarfraz, Kuwait University, Kuwait
  • Ali Mahmood, KPK EZDM, Pakistan
  • Adel Al-Jumaily, University of Technology Sydney, Australia.
  • Nor Shahida, PSU, Saudi Arabia
  • Omar Mubin. Western Sydney University, Australia
  • Rehan Ullah Khan, Qassim University, Saudi Arabia
  • Abdullah Al Mahmud, Swinburne University of Technology, Australia
  • Hany Alashwal, UAE University, UAE
  • Ghulam Mubashar Hassan, UWA, Australia
  • Zia Ur Rehman, JCU, Australia
  • Asif Khan, 20face Enschede, Netherlands
  • Muhammad Uzair, UniSA, Australia
  • Ammar Mahmood, AES, Australia
  • Habib Ullah, University of Hail, Saudi Arabia
  • Monji Kheralla, University of Sfax, Tunisia
  • Hamidah Ibrahim, UPM, Malaysia
  • Avinash Sharma, MMU, India
  • El-Kaber Hachem, MIU, Morocco


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.

Scope and Interests (not limited to)

· 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

Important Dates:

Paper submission deadline: September 19, 2019

Notification of acceptance: October 2, 2019

Camera Ready: October 10, 2019

Conference Dates: November 18 – 22, 2019

Paper Submission Information

All submissions will be handled electronically.

Authors are requested to directly email their double blind paper to the workshop organiser at 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.