A separable neural code in monkey IT enables perfect CAPTCHA decoding
Update: 2021-11-02
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Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2020.04.12.038117v1?rss=1
Authors: Katti, H., Arun, S.
Abstract:
Reading distorted letters is easy for us but so challenging for machine vision that it is used on websites as CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart). How does our brain solve this problem? One solution to have neurons invariant to letter distortions but selective for letter combinations. Another is for neurons to separately encode letter distortions and combinations. Here, we provide evidence for the latter using neural recordings in the monkey inferior temporal cortex. Neurons encoded letter distortions as a product of letter and distortion tuning, and letter combinations as a sum of letters. These rules were sufficient for perfect CAPTCHA decoding, and present in neural networks trained for letter recognition. Thus, a separable neural code enables efficient reading.
Copy rights belong to original authors. Visit the link for more info
http://biorxiv.org/cgi/content/short/2020.04.12.038117v1?rss=1
Authors: Katti, H., Arun, S.
Abstract:
Reading distorted letters is easy for us but so challenging for machine vision that it is used on websites as CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart). How does our brain solve this problem? One solution to have neurons invariant to letter distortions but selective for letter combinations. Another is for neurons to separately encode letter distortions and combinations. Here, we provide evidence for the latter using neural recordings in the monkey inferior temporal cortex. Neurons encoded letter distortions as a product of letter and distortion tuning, and letter combinations as a sum of letters. These rules were sufficient for perfect CAPTCHA decoding, and present in neural networks trained for letter recognition. Thus, a separable neural code enables efficient reading.
Copy rights belong to original authors. Visit the link for more info
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