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.
Additional data and resources
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
If you use any of our data, please cite our paper.
Cracking the neural code of human object vision
European Research CouncilFind out more...