Deep neural network feature maps

Feature maps summaryHere 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 materialAdditional informationFor additional information on the DNNs used, the stimuli images and feature maps extraction procedure please refer to our paper and code.Additional dataset resourcesPlease visit the dataset page for the paper, dataset tutorial, code and more.OSFFor additional data and resources visit our OSF project, where you can find:The stimuli imagesA detailed descriptions of the DNN feature maps data filesCitationsIf you use any of our data, please cite our paper.