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Humans and deep networks largely agree on which kinds of variation make
  object recognition harder

Humans and deep networks largely agree on which kinds of variation make object recognition harder

21 April 2016
Saeed Reza Kheradpisheh
M. Ghodrati
M. Ganjtabesh
T. Masquelier
    OOD
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Papers citing "Humans and deep networks largely agree on which kinds of variation make object recognition harder"

3 / 3 papers shown
Title
Measuring Error Alignment for Decision-Making Systems
Measuring Error Alignment for Decision-Making Systems
Binxia Xu
Antonis Bikakis
Daniel Onah
A. Vlachidis
Luke Dickens
41
0
0
03 Jan 2025
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans
  by measuring error consistency
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency
Robert Geirhos
Kristof Meding
Felix Wichmann
19
116
0
30 Jun 2020
The Roles of Supervised Machine Learning in Systems Neuroscience
The Roles of Supervised Machine Learning in Systems Neuroscience
Joshua I. Glaser
Ari S. Benjamin
Roozbeh Farhoodi
Konrad Paul Kording
18
114
0
21 May 2018
1