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

Data from the paper: Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations. Preprint: https://www.biorxiv.org/content/10.1101/840256v1 Marek A. Pedziwiatr marek.pedziwi@gmail.com September 2020

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Pedziwiatr, Marek A., Kümmerer, Matthias, Wallis, Thomas S.A., Bethge, Matthias, Teufel, Christoph
Format: Dataset
Sprache:eng
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Data from the paper: Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations. Preprint: https://www.biorxiv.org/content/10.1101/840256v1 Marek A. Pedziwiatr marek.pedziwi@gmail.com September 2020
DOI:10.5281/zenodo.3490433