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Deep neural network feature maps
Feature maps summary
Here we release the PCA-downsampled deep neural network (DNN) feature maps used in the data resource paper: "A large and rich EEG dataset for modeling human visual object recognition". We used four DNN architectures (AlexNet, ResNet-50, CORnet-S, MoCo), and extracted their feature map responses to images coming from the THINGS database and from the ILSVRC-2012 challenge.
Useful material
Additional information
For additional information on the DNNs used, the stimuli images and feature maps extraction procedure please refer to our paper and code.
Additional dataset resources
Please visit the dataset page for the paper, dataset tutorial, code and more.
OSF
For additional data and resources visit our OSF project, where you can find:
- The stimuli images
- A detailed descriptions of the DNN feature maps data files
Citations
If you use any of our data, please cite our paper.
Funding
German Research Foundation (DFG) (CI241/1-1)
German Research Foundation (DFG) (CI241/3-1)
German Research Foundation (DFG) (CI241/1-7)
History
Research Institution(s)
Freie Universität BerlinContact email
alessandro.gifford@gmail.comAssociated Preprint DOI
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