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MATRIX Spring Seminar Series – Dr. Amanda Fernandez
March 19, 2021 • 11:00 am - 12:00 pm
On Friday, March 19th, MATRIX is pleased to host Dr. Amanda Fernandez of UTSA as part of our seminar series. More information about Dr. Fernandez’s research may be found on her webpage. All spring seminars will be hosted via Zoom. Full details regarding the seminar may be found below –
Robust Visual Understanding through Segmentation and Saliency Estimation: Challenges in Deep Learning Research
Dr. Amanda Fernandez
Department of Computer Science – UTSA
Friday, March 19, 2021
11 AM -12 PM CST
tinyurl.com/MATRIXSpringSeminar
Computer vision aims to emulate the human visual system, providing artificial intelligence agents with the opportunity to learn from visual data. While the field has evolved significantly over the last 60+ years, more recently deep learning architectures have enabled the transition from processing this visual data to learning how to interpret it. Key research can now focus on how explainable a model is, how well it can understand this input, and how vulnerable that understanding may be to an attack.
In this talk, I will outline some of the state-of-the-art in computer vision, identifying significant research milestones as well as open problems. This talk will take a deep learning perspective, focusing on neural network architectures and research challenges such as few-shot learning, semantic segmentation, and adversarial robustness. Finally, I will discuss some of our recent work applying our vision models to virtual reality/eye tracking, autonomous vehicles, and nuclear physics.