A citation-based method for searching scientific literature

Thomas Serre, Aude Oliva, Tomaso Poggio. Proc Natl Acad Sci U S A 2007
Times Cited: 405







List of co-cited articles
707 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Hierarchical models of object recognition in cortex.
M Riesenhuber, T Poggio. Nat Neurosci 1999
36

Performance-optimized hierarchical models predict neural responses in higher visual cortex.
Daniel L K Yamins, Ha Hong, Charles F Cadieu, Ethan A Solomon, Darren Seibert, James J DiCarlo. Proc Natl Acad Sci U S A 2014
414
26

Speed of processing in the human visual system.
S Thorpe, D Fize, C Marlot. Nature 1996
24

How does the brain solve visual object recognition?
James J DiCarlo, Davide Zoccolan, Nicole C Rust. Neuron 2012
512
23

Deep supervised, but not unsupervised, models may explain IT cortical representation.
Seyed-Mahdi Khaligh-Razavi, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
309
21

Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
19

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.
Radoslaw Martin Cichy, Aditya Khosla, Dimitrios Pantazis, Antonio Torralba, Aude Oliva. Sci Rep 2016
155
16

Representational similarity analysis - connecting the branches of systems neuroscience.
Nikolaus Kriegeskorte, Marieke Mur, Peter Bandettini. Front Syst Neurosci 2008
16

Using goal-driven deep learning models to understand sensory cortex.
Daniel L K Yamins, James J DiCarlo. Nat Neurosci 2016
296
15

Untangling invariant object recognition.
James J DiCarlo, David D Cox. Trends Cogn Sci 2007
335
15


Top-down facilitation of visual recognition.
M Bar, K S Kassam, A S Ghuman, J Boshyan, A M Schmid, A M Dale, M S Hämäläinen, K Marinkovic, D L Schacter, B R Rosen,[...]. Proc Natl Acad Sci U S A 2006
847
12


Fast readout of object identity from macaque inferior temporal cortex.
Chou P Hung, Gabriel Kreiman, Tomaso Poggio, James J DiCarlo. Science 2005
432
11

Resolving human object recognition in space and time.
Radoslaw Martin Cichy, Dimitrios Pantazis, Aude Oliva. Nat Neurosci 2014
253
11


Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition.
Saeed Reza Kheradpisheh, Masoud Ghodrati, Mohammad Ganjtabesh, Timothée Masquelier. Sci Rep 2016
46
23


A toolbox for representational similarity analysis.
Hamed Nili, Cai Wingfield, Alexander Walther, Li Su, William Marslen-Wilson, Nikolaus Kriegeskorte. PLoS Comput Biol 2014
275
11

The dynamics of invariant object recognition in the human visual system.
Leyla Isik, Ethan M Meyers, Joel Z Leibo, Tomaso Poggio. J Neurophysiol 2014
107
10



Matching categorical object representations in inferior temporal cortex of man and monkey.
Nikolaus Kriegeskorte, Marieke Mur, Douglas A Ruff, Roozbeh Kiani, Jerzy Bodurka, Hossein Esteky, Keiji Tanaka, Peter A Bandettini. Neuron 2008
614
10


Representational dynamics of object vision: the first 1000 ms.
Thomas Carlson, David A Tovar, Arjen Alink, Nikolaus Kriegeskorte. J Vis 2013
138
10

Hierarchical Bayesian inference in the visual cortex.
Tai Sing Lee, David Mumford. J Opt Soc Am A Opt Image Sci Vis 2003
506
10

The Psychophysics Toolbox.
D H Brainard. Spat Vis 1997
9


Distributed and overlapping representations of faces and objects in ventral temporal cortex.
J V Haxby, M I Gobbini, M L Furey, A Ishai, J L Schouten, P Pietrini. Science 2001
9

Deep neural networks rival the representation of primate IT cortex for core visual object recognition.
Charles F Cadieu, Ha Hong, Daniel L K Yamins, Nicolas Pinto, Diego Ardila, Ethan A Solomon, Najib J Majaj, James J DiCarlo. PLoS Comput Biol 2014
173
9


Visual objects in context.
Moshe Bar. Nat Rev Neurosci 2004
711
9


Deep Neural Networks as a Computational Model for Human Shape Sensitivity.
Jonas Kubilius, Stefania Bracci, Hans P Op de Beeck. PLoS Comput Biol 2016
73
10

Contextual Feedback to Superficial Layers of V1.
Lars Muckli, Federico De Martino, Luca Vizioli, Lucy S Petro, Fraser W Smith, Kamil Ugurbil, Rainer Goebel, Essa Yacoub. Curr Biol 2015
149
8



Top-down influences on visual processing.
Charles D Gilbert, Wu Li. Nat Rev Neurosci 2013
395
8


Explicit information for category-orthogonal object properties increases along the ventral stream.
Ha Hong, Daniel L K Yamins, Najib J Majaj, James J DiCarlo. Nat Neurosci 2016
103
8

Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks.
Rishi Rajalingham, Elias B Issa, Pouya Bashivan, Kohitij Kar, Kailyn Schmidt, James J DiCarlo. J Neurosci 2018
66
12

Detecting meaning in RSVP at 13 ms per picture.
Mary C Potter, Brad Wyble, Carl Erick Hagmann, Emily S McCourt. Atten Percept Psychophys 2014
92
7


Robust object recognition with cortex-like mechanisms.
Thomas Serre, Lior Wolf, Stanley Bileschi, Maximilian Riesenhuber, Tomaso Poggio. IEEE Trans Pattern Anal Mach Intell 2007
302
7

Neural mechanisms of object recognition.
Maximilian Riesenhuber, Tomaso Poggio. Curr Opin Neurobiol 2002
192
7



Vision as Bayesian inference: analysis by synthesis?
Alan Yuille, Daniel Kersten. Trends Cogn Sci 2006
270
7

Nonparametric statistical testing of EEG- and MEG-data.
Eric Maris, Robert Oostenveld. J Neurosci Methods 2007
7



Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.