Master’s Thesis Presentation • Artificial Intelligence — Towards Pixel-Level OOD Detection for Semantic Segmentation
Matthew Angus, Master’s candidate
David R. Cheriton School of Computer Science
Matthew Angus, Master’s candidate
David R. Cheriton School of Computer Science
Fathiyeh Faghih, School of Electrical and Computer Engineering
University of Tehran
Dmitrii Marin, PhD candidate
David R. Cheriton School of Computer Science
Sharon Choy, PhD candidate
David R. Cheriton School of Computer Science
Hatem Takruri, Master’s candidate
David R. Cheriton School of Computer Science
Siddhartha Sahu, PhD candidate
David R. Cheriton School of Computer Science
Bryce Sandlund, PhD candidate
David R. Cheriton School of Computer Science
Rahul Iyer, Master’s candidate
David R. Cheriton School of Computer Science
Rylo Ashmore, Master’s candidate
David R. Cheriton School of Computer Science
Navid Nasr Esfahani, PhD candidate
David R. Cheriton School of Computer Science
Linear All-or-nothing Transforms are unconditionally secure cryptographic tools with various applications, for example, in secure distributed storage and secure network coding.