AI & ACRA 2015 Workshop and Tutorial on Deep Learning and its Applications in Vision and Robotics

A full day workshop held on the December 1 in Canberra, Australia.


The webpage for this workshop is here:

http://juxi.net/workshop/deeplearning-applications-vision-robotics-2015/


About the workshop

The following is a non exhaustive list of topics of interest: 

  • Novel deep learning architectures, models, and learning algorithms
  • Multimodal deep learning methods such as vision, speech, language, control
  • Unsupervised deep learning
  • Deep learning for decision making and control
  • Deep reinforcement learning
  • Applications of deep models to problems in vision and robotics,
    such as:
    • Activity recognition
    • Large scale image classification in real world/robotic settings
    • Robot control

Motivation

Applications of convolutional neural networks and deep learning methods have been proliferating at an astronomical rate in the recent times into various disciplines of engineering. The significant advancements that deep learning methods have brought out for large scale image classification tasks have generated a surge of excitement in applying the techniques to other problems in computer vision and more broadly into other disciplines of computer science, such as robotics. However, building deep learning algorithms for highly non-linear real-world problems such as those encountered in computer vision and robotics is non-trivial and requires substantial expertise.
The goal of this workshop is to bring together researchers from Australia and Asia working in the field of deep learning to discuss recent advances, ongoing developments, and build collaborations by exchanging new ideas for future applications. Submissions will form the basis for spotlight talks and poster discussions.

Organizers 

The workshop is organized by Juxi Leitner (Unlicensed) (Queensland University of Technology), Anoop Cherian (Unlicensed) (Australian National University) and Sareh Shirazi (Unlicensed) (Queensland University of Technology).