[visionlist] Postdoc position in computational modeling of human object recognition at NYU
denis.pelli at nyu.edu
Sun Nov 11 17:54:55 -05 2018
Announcing a 3-year postdoctoral research position in Denis Pelli's lab at
NYU in Psychology, affiliated with Center for Neural Science, supported by
NIH grant to Denis Pelli (PI), Jon Winawer, & Yann LeCun, in computational
modeling of human object recognition in clutter. Crowding is a
computational bottleneck in human object recognition. Is crowding just a
nuisance, or is it the key to understanding how an object is recognized by
a limited number of neurons? A trained ConvNet mimics many aspects of human
letter recognition within a single crowding unit (Ziskind et al. 2014
<http://f1000.com/posters/browse/summary/1095738>). However, some things
cannot be recognized by people unless they extend across several crowding
units, and human learning generalizes across scale and other dimensions.
We’d like to extend our modeling of object recognition to explain that.
Ongoing results on efficiency (contrast thresholds in noise) and the need
for several crowding units provide modeling clues (Pelli 2018
fMRI collaboration with Winawer’s lab is documenting conservation of
crowding distance in area V4 (Zhou et al. 2018
Pelli’s lab is in the Psychology Dept., on the same elevator as the Center
for Neural Science and our 3T magnet, two blocks from Courant and Facebook.
Salary will be $48,432 or higher, based on experience.
For informal inquiries, email denis.pelli at nyu.edu
To apply, please visit: https://apply.interfolio.com/53970
Ziskind, A.J., Hénaff, O., LeCun, Y., & Pelli, D.G. (2014) The bottleneck
in human letter recognition: A computational model. Vision Sciences
Society, St. Pete Beach, Florida, May 16-21, 2014, 56.583.
D. Pelli (2018) Despite a 100-fold drop in cortical magnification, a
fixed-size letter is recognized equally well at eccentricities of 0 to 20
deg. How can this be?. *Journal of Vision* 2018;18(10):26.
J. Zhou, N. Benson, J. Winawer, D. Pelli (2018) Conservation of crowding
distance in human V4. *Journal of Vision*2018;18(10):856.
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