Psychophysics may be the game-changer for deep neural networks (DNNs) to imitate the human vision

Behavioral and Brain Sciences 46:e388 (2023)
  Copy   BIBTEX

Abstract

Psychologically faithful deep neural networks (DNNs) could be constructed by training with psychophysics data. Moreover, conventional DNNs are mostly monocular vision based, whereas the human brain relies mainly on binocular vision. DNNs developed as smaller vision agent networks associated with fundamental and less intelligent visual activities, can be combined to simulate more intelligent visual activities done by the biological brain.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 91,435

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Neural networks, AI, and the goals of modeling.Walter Veit & Heather Browning - 2023 - Behavioral and Brain Sciences 46:e411.

Analytics

Added to PP
2023-12-08

Downloads
10 (#1,179,038)

6 months
10 (#257,636)

Historical graph of downloads
How can I increase my downloads?

Citations of this work

No citations found.

Add more citations

References found in this work

Computing machinery and intelligence.Alan M. Turing - 1950 - Mind 59 (October):433-60.
The Society of Mind.Marvin Minsky - 1987 - The Personalist Forum 3 (1):19-32.

Add more references