Uncovering high-level visual cortex preferences by training convolutional 
neural networks on large neuroimaging data

Seeliger, Katja; Leipe, Roman; Roth, Johannes; Hebart, Martin N.

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Uncovering high-level visual cortex preferences by training convolutional neural networks on large neuroimaging data

Seeliger, K., Leipe, R., Roth, J., & Hebart, M. N. (2023). Uncovering high-level visual cortex preferences by training convolutional neural networks on large neuroimaging data. Poster presented at Neuro-AI-Talks (NEAT), Osnabrück, Germany.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000E-761C-F Version Permalink: https://hdl.handle.net/21.11116/0000-000E-761D-E

Genre: Poster

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Creators:
Seeliger, Katja¹, Author
Leipe, Roman, Author
Roth, Johannes¹, 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: 2023-09-25

Publication Status: Not specified

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Title: Neuro-AI-Talks (NEAT)

Place of Event: Osnabrück, Germany

Start-/End Date: 2023-09-24 - 2023-09-25

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