Clarifying status of DNNs as models of human vision

Article Properties
  • Language
    English
  • Publication Date
    2023/01/01
  • Indian UGC (journal)
  • Refrences
    86
  • Jeffrey S. Bowers ORCID (unauthenticated)
  • Gaurav Malhotra
  • Marin Dujmović
  • Milton L. Montero
  • Christian Tsvetkov
  • Valerio Biscione
  • Guillermo Puebla
  • Federico Adolfi
  • John E. Hummel
  • Rachel F. Heaton
  • Benjamin D. Evans
  • Jeffrey Mitchell
  • Ryan Blything
Abstract
Cite
Bowers, Jeffrey S., et al. “Clarifying Status of DNNs As Models of Human Vision”. Behavioral and Brain Sciences, vol. 46, 2023, https://doi.org/10.1017/s0140525x23002777.
Bowers, J. S., Malhotra, G., Dujmović, M., Montero, M. L., Tsvetkov, C., Biscione, V., Puebla, G., Adolfi, F., Hummel, J. E., Heaton, R. F., Evans, B. D., Mitchell, J., & Blything, R. (2023). Clarifying status of DNNs as models of human vision. Behavioral and Brain Sciences, 46. https://doi.org/10.1017/s0140525x23002777
Bowers JS, Malhotra G, Dujmović M, Montero ML, Tsvetkov C, Biscione V, et al. Clarifying status of DNNs as models of human vision. Behavioral and Brain Sciences. 2023;46.
Refrences
Title Journal Journal Categories Citations Publication Date
Lost in latent space: Examining failures of disentangled models at combinatorial generalisation 2022
Unsupervised causal generative understanding of images 2022
Diverse deep neural networks all predict human inferior temporal cortex well, after training and fitting 2021
The origins and prevalence of texture bias in convolutional neural networks 2020
Humans can decipher adversarial images 2019