Simone Smarr
Papers
1
Total Citations
5
H-Index
1
About
Simone Smarr’s research explores the critical intersection of human cognition and computational image analysis, with a focus on trust factors that shape how experts and non-experts interpret visual data. Her most-cited work, “Human Trust Factors in Image Analysis” (2018), has garnered 5 citations and examines the psychological and contextual elements—such as prior experience, interface design, and algorithmic transparency—that influence reliance on automated image interpretation systems. This foundational study contributes to the growing field of human-computer interaction, particularly in medical imaging and remote sensing, where trust in AI-driven outputs can determine diagnostic accuracy or operational decisions. Smarr’s work highlights the nuanced ways human bias and confidence interact with machine-generated results, offering practical insights for designing more trustworthy and user-centered analytical tools. While her citation count is modest, her research addresses a timely and underexplored area, laying groundwork for future studies on human-AI collaboration in visual tasks. Smarr’s contributions are especially relevant for students and researchers interested in cognitive ergonomics, decision-making under uncertainty, and the ethical deployment of AI in high-stakes environments.
Research Focus
Key Achievements
Top Papers
- 1Human Trust Factors in Image Analysis5 citations · 2018