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Courtney Spoerer
Courtney Spoerer
Medical Research Council, Cognition and Brain Sciences Unit
Verified email at mrc-cbu.cam.ac.uk
Title
Cited by
Cited by
Year
Recurrence is required to capture the representational dynamics of the human visual system
TC Kietzmann, CJ Spoerer, LKA Sörensen, RM Cichy, O Hauk, ...
Proceedings of the National Academy of Sciences 116 (43), 21854-21863, 2019
1912019
Recurrent convolutional neural networks: a better model of biological object recognition
CJ Spoerer, P McClure, N Kriegeskorte
Frontiers in psychology 8, 1551, 2017
1732017
Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision
CJ Spoerer, TC Kietzmann, J Mehrer, I Charest, N Kriegeskorte
PLoS computational biology 16 (10), e1008215, 2020
57*2020
Individual differences among deep neural network models
J Mehrer, CJ Spoerer, N Kriegeskorte, TC Kietzmann
Nature communications 11 (1), 1-12, 2020
552020
An ecologically motivated image dataset for deep learning yields better models of human vision
J Mehrer, CJ Spoerer, EC Jones, N Kriegeskorte, TC Kietzmann
Proceedings of the National Academy of Sciences 118 (8), e2011417118, 2021
322021
A computational exploration of complementary learning mechanisms in the primate ventral visual pathway
CJ Spoerer, A Eguchi, SM Stringer
Vision Research 119, 16-28, 2016
62016
Corrigendum: recurrent convolutional neural networks: a better model of biological object recognition
CJ Spoerer, P McClure, N Kriegeskorte
Frontiers in Psychology 9, 1695, 2018
22018
Recurrent convolutional neural networks as models of biological object recognition
C Spoerer
University of Cambridge, 2020
2020
Recurrent convolutional neural networks suppress occluders and enhance targets in occluded object recognition
CJ Spoerer, N Kriegeskorte
Conference on Cognitive Computational Neuroscience, 2017
2017
Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition Download PDF
CJ Spoerer, P McClure, N Kriegeskorte
Representational dynamics in the human ventral stream captured in deep recurrent neural nets
TC Kietzmann, CJ Spoerer, L Sörensen, RM Cichy, O Hauk, ...
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Articles 1–11