11 citations · 17 across the 3 of their papers we have counts for
3 papers
cs.CV2019
Assessment of Faster R-CNN in Man-Machine collaborative search
Arturo Deza, Amit Surana, Miguel P. Eckstein
With the advent of modern expert systems driven by deep learning that supplement human experts (e.g. radiologists, dermatologists, surveillance scanners), we analyze how and when d…
cs.HC2017★ 11 cited
Attention Allocation Aid for Visual Search
Arturo Deza, Jeffrey R. Peters, Grant S. Taylor +2
This paper outlines the development and testing of a novel, feedback-enabled attention allocation aid (AAAD), which uses real-time physiological data to improve human performance i…
cs.CV2016★ 6 cited
Can Peripheral Representations Improve Clutter Metrics on Complex Scenes?
Arturo Deza, Miguel P. Eckstein
Previous studies have proposed image-based clutter measures that correlate with human search times and/or eye movements. However, most models do not take into account the fact that…