Meeting Abstract

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


Authors listDobs, K.; Yuan, J.; Martinez, J.; Kanwisher, N

Appeared inTeaP 2021 : abstracts of the 63th Conference of Experimental Psychologists

Editor listHuckauf, A.; Baumann, M.; Ernst, M.; Herbert, C.; Kiefer, M.; Sauter, M.

Publication year2021

Pages61-62

DOI Linkhttps://doi.org/10.23668/psycharchives.5178

Conference63th Conference of Experimental Psychologists (TeaP 2021)



Authors/Editors




Citation Styles

Harvard Citation styleDobs, K., Yuan, J., Martinez, J. and Kanwisher, N. (2021) Using task-optimized neural networks to understand how experience might shape human face perception, in Huckauf, A., Baumann, M., Ernst, M., Herbert, C., Kiefer, M. and Sauter, M. (eds.) TeaP 2021 : abstracts of the 63th Conference of Experimental Psychologists. Ulm. pp. 61-62. https://doi.org/10.23668/psycharchives.5178

APA Citation styleDobs, K., Yuan, J., Martinez, J., & Kanwisher, N. (2021). Using task-optimized neural networks to understand how experience might shape human face perception. In Huckauf, A., Baumann, M., Ernst, M., Herbert, C., Kiefer, M., & Sauter, M. (Eds.), TeaP 2021 : abstracts of the 63th Conference of Experimental Psychologists. (pp. 61-62). https://doi.org/10.23668/psycharchives.5178


Last updated on 2025-21-05 at 16:14