Author

S. Ghebreab

University of AmsterdamORCID 0009-0007-5788-4635Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1 Research Focus:gene regulatory network inference· 1 Assay:imaging· 1

Frequent Co-Authors

H. Steven ScholteiD· 2 shared Iris I. A. GroeniD· 2 shared Arnold W. M. Smeulders· 1 shared Kandan RamakrishnaniD· 1 shared Noor SeijdeliD· 1 shared Sara JahfariiD· 1 shared Victor A. F. LammeiD· 1 shared

Activity by Year

2017-2018 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 15 mutual co-author links

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2 shared papersNeuroscience

H. Steven ScholteORCID

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2 papers

Recent·Most cited

Scene complexity modulates degree of feedback activity during object recognition in natural scenes

Iris I. A. Groen, Sara Jahfari, Noor Seijdel, S. Ghebreab, Victor A. F. Lamme, H. Steven Scholte

The paper shows that feedback activity in the brain increases during object recognition in complex natural scenes, improving performance, while feed-forward processing suffices for simpler scenes.

PLoS Computational Biology · Dec 31, 2018Peer-reviewedNeuroscience

Characterizing the temporal dynamics of object recognition by deep neural networks: role of depth

Kandan Ramakrishnan, Iris I. A. Groen, Arnold W. M. Smeulders, H. Steven Scholte, S. Ghebreab

This study examines how the depth of convolutional neural networks (CNNs) correlates with EEG responses during visual object recognition, showing that deeper CNNs improve predictions after 150 ms.

bioRxiv · Sep 10, 2017 · PreprintNeuroscience