Events

Marcus Brubaker
Department of Electrical Engineering and Computer Science, York University
Research Director, Borealis AI

Modelling and synthesizing image noise is an important aspect in many computer vision applications. The long-standing additive white Gaussian and heteroscedastic (signal-dependent) noise models widely used in the literature provide only a coarse approximation of real sensor noise.

Dmitrii Pasechnik, Department of Computer Science
University of Oxford

Daniel Gibney, Department of Computer Science
University of Central Florida

James Jacobs, Co-founder and CEO
Ziva Dynamics

Richard Peng, School of Computer Science
Georgia Institute of Technology

Vedat Levi Alev, PhD candidate
David R. Cheriton School of Computer Science

Aravind Machiry, Department of Computer Science
University of California, Santa Barbara

Please note: This seminar series has two speakers.

Mathieu Nancel
Loki Research Group
Inria Lille, France

Aastha Mehta, Max Planck Institute for Software Systems
Saarbrücken, Germany

Tiasa Mondol, Master’s candidate
David R. Cheriton School of Computer Science