May ’23 Computer Vision Meetup
May 11, 2023 – 10AM PT
May 11, 2023 – 10AM PT
Virtual / Zoom
- The Role of Symmetry in Human and Computer Vision – Sven Dickinson (University of Toronto & Samsung)
- Machine Learning for Fast, Motion-Robust MRI – Nalini Singh (MIT)
- Closing Remarks
The Role of Symmetry in Human and Computer Vision
Symmetry is one of the most ubiquitous regularities in our natural world. For almost 100 years, human vision researchers have studied how the human vision system has evolved to exploit this powerful regularity as a basis for grouping image features. While computer vision is a much younger discipline, the trajectory is similar, with symmetry playing a major role in both perceptual grouping and object representation. After briefly reviewing some of the milestones in symmetry-based perceptual grouping and object representation/recognition in both human and computer vision, I will review our efforts that draw on computer vision to understand the role that symmetry plays in human scene perception. Conversely, I will also look at how these results in human scene perception can strengthen the performance of modern deep learning computer vision systems for scene perception.
Sven Dickinson is Professor of Computer Science at the University of Toronto, and is also Vice President and Head of the new Samsung Toronto AI Research Center. Learn more about his research and publications.
Machine Learning for Fast, Motion-Robust MRI
Magnetic resonance imaging (MRI) is a powerful imaging modality that enables detailed visualization of tissue content and structure. However, MRI suffers from long acquisition times and significant susceptibility to motion artifacts. This talk will explore deep learning approaches that incorporate imaging physics to produce high-quality MR images from highly accelerated and/or motion-corrupted data.
Nalini Singh is a Ph.D. student at the Harvard-MIT Program in Health Sciences and Technology, working in the Medical Vision Group at the MIT Computer Science and Artificial Intelligence Laboratory. Her primary research interests are in medical image reconstruction and analysis, signal processing, and inverse problems.
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