Cargando…
Implementation-Independent Representation for Deep Convolutional Neural Networks and Humans in Processing Faces
Deep convolutional neural networks (DCNN) nowadays can match human performance in challenging complex tasks, but it remains unknown whether DCNNs achieve human-like performance through human-like processes. Here we applied a reverse-correlation method to make explicit representations of DCNNs and hu...
Autores principales: | Song, Yiying, Qu, Yukun, Xu, Shan, Liu, Jia |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7870475/ https://www.ncbi.nlm.nih.gov/pubmed/33574746 http://dx.doi.org/10.3389/fncom.2020.601314 |
Ejemplares similares
-
The Face Inversion Effect in Deep Convolutional Neural Networks
por: Tian, Fang, et al.
Publicado: (2022) -
Multidimensional Face Representation in a Deep Convolutional Neural Network Reveals the Mechanism Underlying AI Racism
por: Tian, Jinhua, et al.
Publicado: (2021) -
The Face Module Emerged in a Deep Convolutional Neural Network Selectively Deprived of Face Experience
por: Xu, Shan, et al.
Publicado: (2021) -
Emerged human-like facial expression representation in a deep convolutional neural network
por: Zhou, Liqin, et al.
Publicado: (2022) -
Non-uniqueness Phenomenon of Object Representation in Modeling IT Cortex by Deep Convolutional Neural Network (DCNN)
por: Dong, Qiulei, et al.
Publicado: (2020)