Gregor Koporec
Papers
1
Total Citations
5
H-Index
1
About
Gregor Koporec is a researcher whose work lies at the intersection of deep learning, computer vision, and real-world robotics, with a particular focus on overcoming the challenges of dynamic, human-inhabited environments. His most cited work, "Deep Learning Performance in the Presence of Significant Occlusions - An Intelligent Household Refrigerator Case" (2019), tackles a fundamental problem in applied AI: how deep learning models can maintain robust performance when objects are heavily obstructed. By using the intelligent refrigerator as a case study, Koporec highlights the gap between controlled lab conditions and messy, everyday settings where humans and robots interact. His research explores how biological systems—like humans changing their viewpoint or using hands to manipulate a scene—can inspire more resilient machine perception. While his citation count is still growing, this work has garnered attention for its practical relevance to domestic robotics and autonomous systems. Koporec’s contributions are particularly valuable for students and engineers seeking to deploy computer vision in environments where occlusion is the norm, not the exception, making his research a stepping stone toward truly adaptive, real-world AI.
Research Focus
Key Achievements
Top Papers
- 1