Comprehensive assessment methods are key to progress in deep learning

Bowers et al. eloquently describe issues with current deep neural network (DNN) models of vision, claiming that there are deficits both with the methods of assessment, and with the models themselves. I am in agreement with both these claims, but propose a different recipe to the one outlined in the...

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Bibliographic Details
Published in:The Behavioral and brain sciences 2023-12, Vol.46, p.e407-e407, Article e407
Main Author: Spratling, Michael W.
Format: Article
Language:English
Subjects:
Brain research
Deep learning
Experiments
Neural networks
Neurosciences
Open Peer Commentary
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Online Access:Get full text
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Summary:Bowers et al. eloquently describe issues with current deep neural network (DNN) models of vision, claiming that there are deficits both with the methods of assessment, and with the models themselves. I am in agreement with both these claims, but propose a different recipe to the one outlined in the target article for overcoming these issues.
ISSN:0140-525X
1469-1825
DOI:10.1017/S0140525X23001668