Deep Learning: Applications and Recent Directions

Hosted by Zeev Zalevsky, Editor in Chief of the Journal of Electronic Imaging, this webinar on Deep Learning: Applications and Recent Directions covered exciting recent applications for deep learning, including autonomous driving perception, geometric deep learning, few shot learning, and studies of ancient Babylonia. A recording of the event is archived below.

Deep Learning: Applications and Recent Directions

Thursday, 9 December 2021

6 a.m. PDT/9 a.m. EDT/2 p.m. GMT/10 p.m. CST

In the last decade, deep learning has become a predominant approach in machine learning and improved the state of the art on many tasks in many domains by a considerable margin. Hosted by JEI Editor-in-Chief Zeev Zalevsky of Bar-Ilan University and moderated by Thomas Kipf of Google Brain, this webinar will present six short talks on deep learning applications by experts from academia and industry. The topics will cover a wide breadth of applications, from autonomous driving to digital humanities, and in various settings such as few-shot learning and federated learning.

Speakers:

Ethan Fetaya, Bar-Ilan University: "Federated Learning: Deep Learning on Edge Devices"
Dan Levi, General Motors R&D: "Data Efficient Training Strategies for Automated Driving Perception"
Haggai Marron, NVIDIA: "Geometric Deep Learning: Learning on Graphs, Surfaces, and Point Clouds"
Renjie Liao, Google Brain/University of British Columbia: "Injecting Structures Into Deep Learning: A Case Study of Image Generation"
Eleni Triantafillou, Google Brain: "Recent Progress and Challenges in Few-Shot Classification"
Shai Gordon, Ariel University: "The Babylonian Engine: Studying Ancient Babylonia using OCR, NLP, and ML"

Deep Learning: Applications and Recent Directions