Alexander V. Golovan
Papers
1
Total Citations
8
H-Index
1
About
Alexander V. Golovan is a researcher whose work lies at the intersection of computer vision, biologically inspired perception, and cognitive modeling. His most influential contribution is the development of the MARR (Multiresolutional Attentional Representation and Recognition) model, an active vision system grounded in the scanpath theory of Noton and Stark. This model, detailed in his 1997 paper, offers a biologically plausible framework for invariant recognition of gray-level images, mimicking how the human visual system actively explores and interprets scenes. While his most-cited paper has garnered 8 citations, its conceptual impact is significant, bridging neuroscience and computational vision. Golovan’s work is notable for its early integration of attention mechanisms into machine vision, predating the modern deep learning era’s focus on attention. His research continues to inspire those interested in how active perception and multiresolutional processing can lead to more robust and human-like visual recognition systems.
Research Focus
Key Achievements
Top Papers
- 1<title>MARR: active vision model</title>8 citations · 1997