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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

The Limits of Feedforward Vision: Recurrent Processing Promotes Robust Object Recognition when Objects Are Degraded
Dean Wyatte, Tim Curran, Randall C. O’Reilly
Journal of Cognitive Neuroscience (2012) Vol. 24, Iss. 11, pp. 2248-2261
Open Access | Times Cited: 113

Showing 1-25 of 113 citing articles:

Deep learning in neural networks: An overview
Jürgen Schmidhuber
Neural Networks (2014) Vol. 61, pp. 85-117
Open Access | Times Cited: 16707
Human Pose Estimation with Iterative Error Feedback
João Carreira, Pulkit Agrawal, Katerina Fragkiadaki, et al.
(2016), pp. 4733-4742
Open Access | Times Cited: 753
Cognitive computational neuroscience
Nikolaus Kriegeskorte, Pamela K. Douglas
Nature Neuroscience (2018) Vol. 21, Iss. 9, pp. 1148-1160
Open Access | Times Cited: 470
Recurrence is required to capture the representational dynamics of the human visual system
Tim C. Kietzmann, Courtney J. Spoerer, Lynn K. A. Sörensen, et al.
Proceedings of the National Academy of Sciences (2019) Vol. 116, Iss. 43, pp. 21854-21863
Open Access | Times Cited: 376
Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition
Courtney J. Spoerer, Patrick McClure, Nikolaus Kriegeskorte
Frontiers in Psychology (2017) Vol. 8
Open Access | Times Cited: 211
Recurrent computations for visual pattern completion
Hanlin Tang, Martin Schrimpf, William Lotter, et al.
Proceedings of the National Academy of Sciences (2018) Vol. 115, Iss. 35, pp. 8835-8840
Open Access | Times Cited: 207
Deep Neural Networks in Computational Neuroscience
Tim C. Kietzmann, Patrick McClure, Nikolaus Kriegeskorte
Oxford Research Encyclopedia of Neuroscience (2019)
Open Access | Times Cited: 175
Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition
Saeed Reza Kheradpisheh, Masoud Ghodrati, ‎Mohammad Ganjtabesh, et al.
Scientific Reports (2016) Vol. 6, Iss. 1
Open Access | Times Cited: 175
Contextual Priming and Feedback for Faster R-CNN
Abhinav Shrivastava, Abhinav Gupta
Lecture notes in computer science (2016), pp. 330-348
Closed Access | Times Cited: 170
Inhibitory stabilization and cortical computation
Sadra Sadeh, Claudia Clopath
Nature reviews. Neuroscience (2020) Vol. 22, Iss. 1, pp. 21-37
Closed Access | Times Cited: 165
Recurrent Processing during Object Recognition
Randall C. O’Reilly, Dean Wyatte, Seth Herd, et al.
Frontiers in Psychology (2013) Vol. 4
Open Access | Times Cited: 176
Deep Networks with Internal Selective Attention through Feedback Connections
Marijn Stollenga, Jonathan Masci, Faustino Gomez, et al.
Neural Information Processing Systems (2014) Vol. 27, pp. 3545-3553
Closed Access | Times Cited: 127
Early recurrent feedback facilitates visual object recognition under challenging conditions
Dean Wyatte, David J. Jilk, Randall C. O’Reilly
Frontiers in Psychology (2014) Vol. 5
Open Access | Times Cited: 125
Feedback Networks
Amir Zamir, Te-Lin Wu, Lin Sun, et al.
Computer Vision and Pattern Recognition (2017)
Closed Access | Times Cited: 120
Feedback Networks
Amir Zamir, Te-Lin Wu, Lin Sun, et al.
(2017), pp. 1808-1817
Closed Access | Times Cited: 118
Deep Networks with Internal Selective Attention through Feedback Connections
Marijn Stollenga, Jonathan Masci, Faustino Gomez, et al.
arXiv (Cornell University) (2014)
Closed Access | Times Cited: 114
Beyond core object recognition: Recurrent processes account for object recognition under occlusion
Karim Rajaei, Yalda Mohsenzadeh, Reza Ebrahimpour, et al.
PLoS Computational Biology (2019) Vol. 15, Iss. 5, pp. e1007001-e1007001
Open Access | Times Cited: 102
Human Pose Estimation with Iterative Error Feedback
João Carreira, Pulkit Agrawal, Katerina Fragkiadaki, et al.
arXiv (Cornell University) (2015)
Closed Access | Times Cited: 97
Neural representation for object recognition in inferotemporal cortex
Sidney R. Lehky, Keiji Tanaka
Current Opinion in Neurobiology (2016) Vol. 37, pp. 23-35
Closed Access | Times Cited: 97
Hybrid predictive coding: Inferring, fast and slow
Alexander Tscshantz, Beren Millidge, Anil K. Seth, et al.
PLoS Computational Biology (2023) Vol. 19, Iss. 8, pp. e1011280-e1011280
Open Access | Times Cited: 31
Cognitive unbinding: A neuroscientific paradigm of general anesthesia and related states of unconsciousness
George A. Mashour
Neuroscience & Biobehavioral Reviews (2013) Vol. 37, Iss. 10, pp. 2751-2759
Open Access | Times Cited: 89
Top-Down Feedback Controls the Cortical Representation of Illusory Contours in Mouse Primary Visual Cortex
Alexandr Pak, Esther Ryu, Claudia Li, et al.
Journal of Neuroscience (2019) Vol. 40, Iss. 3, pp. 648-660
Open Access | Times Cited: 72
Neuroimaging Findings on Amodal Completion: A Review
Jordy Thielen, Sander Bosch, Tessa M. van Leeuwen, et al.
i-Perception (2019) Vol. 10, Iss. 2
Open Access | Times Cited: 71
Overcoming Occlusion in the Automotive Environment—A Review
Shane Gilroy, Edward Jones, Martin Glavin
IEEE Transactions on Intelligent Transportation Systems (2020) Vol. 22, Iss. 1, pp. 23-35
Closed Access | Times Cited: 64
Deep Neural Networks in Computational Neuroscience
Tim C. Kietzmann, Patrick McClure, Nikolaus Kriegeskorte
bioRxiv (Cold Spring Harbor Laboratory) (2017)
Open Access | Times Cited: 63
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