Dimensions that matter: Interpretable object dimensions in humans and deep 
neural networks

Mahner, Florian; Muttenthaler, Lukas; Güçlü, U.; Hebart, Martin N.

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Dimensions that matter: Interpretable object dimensions in humans and deep neural networks

Mahner, F., Muttenthaler, L., Güçlü, U., & Hebart, M. N. (2023). Dimensions that matter: Interpretable object dimensions in humans and deep neural networks. Poster presented at 6th Annual Conference on Cognitive Computational Neuroscience (CCN), Oxford, United Kingdom.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000E-7612-9 Version Permalink: https://hdl.handle.net/21.11116/0000-000E-7613-8

Genre: Poster

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Creators:
Mahner, Florian¹, Author
Muttenthaler, Lukas¹, Author
Güçlü, U., Author
Hebart, Martin N.¹, Author

Affiliations:
1Max Planck Research Group Vision and Computational Cognition, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_3158378

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Language(s): eng - English

Dates: Created: 2023-08-25

Publication Status: Not specified

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Title: 6th Annual Conference on Cognitive Computational Neuroscience (CCN)

Place of Event: Oxford, United Kingdom

Start-/End Date: 2023-08-24 - 2023-08-27

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