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Comment
. 2018 Jan 19:12:4.
doi: 10.3389/fncom.2018.00004. eCollection 2018.

Commentary: Using goal-driven deep learning models to understand sensory cortex

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Comment

Commentary: Using goal-driven deep learning models to understand sensory cortex

Qiulei Dong et al. Front Comput Neurosci. .
No abstract available

Keywords: IT neuron; categorization; convergent features; goal-driven deep learning models; hierarchical convolutional neural network.

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References

    1. Hong H., Yamins D. L., Majaj N. J., DiCarlo J. J. (2016). Explicit information for category-orthogonal object properties increases along the ventral stream. Nat. Neurosci. 19, 613–622. 10.1038/nn.4247 - DOI - PubMed
    1. Khaligh-Razavi S., Kriegeskorte N. (2014). Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation. PLOS Comput. Biol. 10:e1003915. 10.1371/journal.pcbi.1003915 - DOI - PMC - PubMed
    1. Krizhevsky A., Sutskever I., Hinton G. E. (2012). ImageNet classification with deep convolutional neural networks, In Proceeding of Advances in Neural Information Processing Systems 25 (Lake Tahoe: ). 1106–1114.
    1. LeCun Y., Bengio Y., Hinton G. (2015). Deep learning. Nature 521, 436–444. 10.1038/nature14539 - DOI - PubMed
    1. Li Y., Yosinski J., Clune J., Lipson H., Hopcroft J. (2016). Convergent Learning: do different neural networks learn the same representations? arXiv:1511.07543v3.

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