Author

Matthias Kümmerer

University of TübingenORCID 0000-0001-9644-4703Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:spatial domain detection· 1 Approach:statistical model· 1

Frequent Co-Authors

Christoph TeufeliD· 2 shared Marek A. PedziwiatriD· 2 shared Matthias BethgeiD· 2 shared Thomas S. A. WallisiD· 2 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersNeuroscience

Christoph TeufelORCID

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2 papers

Recent·Most cited

NeuroscienceJournal of VisionPeer-reviewedFeb 16, 2022

Semantic object-scene inconsistencies affect eye movements, but not in the way predicted by contextualized meaning maps

Marek A. Pedziwiatr, Matthias Kümmerer, Thomas S. A. Wallis…·Christoph Teufel

The paper shows that semantically inconsistent objects attract more fixations than consistent ones, but contextualized meaning maps fail to capture this relationship.

7 citations

imagingstatistical model

𝕏 PostBluesky

NeuroscienceCognitionPeer-reviewedOct 20, 2020

Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations

Marek A. Pedziwiatr, Matthias Kümmerer, Thomas S. A. Wallis…·Christoph Teufel

This study compares meaning maps and saliency models in predicting human fixations, finding that deep neural networks outperform meaning maps in accuracy and responsiveness to meaning changes.

33 citations

imagingdeep learning

𝕏 PostBluesky