Using task-optimized neural networks to understand how experience might shape human face perception - Forschungsportal der Justus-Liebig-Universität Gießen:

Meeting Abstract

Using task-optimized neural networks to understand how experience might shape human face perception

Autorenliste: Dobs, K.; Yuan, J.; Martinez, J.; Kanwisher, N.

Jahr der Veröffentlichung: 2021

Zeitschrift: Journal of Vision

Bandnummer: 21

Heftnummer: 9

DOI Link: https://doi.org/10.1167/jov.21.9.2292

Konferenz: 21th Vision Sciences Society Annual Meeting (VSS 2021)

Verlag: Association for Research in Vision and Ophthalmology

Autoren/Herausgeber

- Dr. Katharina Barbara Dobs

Zitierstile

Harvard-Zitierstil: Dobs, K., Yuan, J., Martinez, J. and Kanwisher, N. (2021) Using task-optimized neural networks to understand how experience might shape human face perception, Journal of Vision, 21(9), Article 2292. https://doi.org/10.1167/jov.21.9.2292

APA-Zitierstil: Dobs, K., Yuan, J., Martinez, J., & Kanwisher, N. (2021). Using task-optimized neural networks to understand how experience might shape human face perception. Journal of Vision. 21(9), Article 2292. https://doi.org/10.1167/jov.21.9.2292