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Scale and translation-invariance for novel objects in human vision. Scientific Reports 10, (2020).
s41598-019-57261-6.pdf (1.46 MB)
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Eccentricity Dependent Neural Network with Recurrent Attention for Scale, Translation and Clutter Invariance . Vision Science Society (2019).
Properties of invariant object recognition in human one-shot learning suggests a hierarchical architecture different from deep convolutional neural networks. Vision Science Society (2019).
Properties of invariant object recognition in human oneshot learning suggests a hierarchical architecture different from deep convolutional neural networks . Vision Science Society (2019). doi:10.1167/19.10.28d
Do Deep Neural Networks Suffer from Crowding?. (2017).
CBMM-Memo-069.pdf (6.47 MB)
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Eccentricity Dependent Deep Neural Networks for Modeling Human Vision. Vision Sciences Society (2017).
Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision. AAAI Spring Symposium Series, Science of Intelligence (2017). at <https://www.aaai.org/ocs/index.php/SSS/SSS17/paper/view/15360>
paper.pdf (963.87 KB)
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On the Human Visual System Invariance to Translation and Scale. Vision Sciences Society (2017).
Is the Human Visual System Invariant to Translation and Scale?. AAAI Spring Symposium Series, Science of Intelligence (2017).
Foveation-based Mechanisms Alleviate Adversarial Examples. (2016).
cbmm_memo_044.pdf (11.48 MB)
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