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Deep neural network feature maps

dataset
posted on 2022-11-09, 23:37 authored by Alessandro GiffordAlessandro Gifford

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

Cracking the neural code of human object vision

European Research Council

Find out more...

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 Universit├Ąt Berlin

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