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

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

4 / 4 papers shown

Title
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 Robert Geirhos Kristof Meding Felix Wichmann 19 117 0 30 Jun 2020
Distinguishing mirror from glass: A 'big data' approach to material perception Hideki Tamura Konrad E. Prokott R. Fleming OOD AAML 17 9 0 05 Mar 2019
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