Predicting population neural activity in the Algonauts challenge using end-to-end trained Siamese networks and group convolutions

arxiv(2020)

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摘要
The Algonauts challenge is about predicting the object representations in the form of Representational Dissimilarity Matrices (RDMS) derived from visual brain regions. We used a customized deep learning model using the concept of Siamese networks and group convolutions to predict neural distances corresponding to a pair of images. Training data was best explained by distances computed over the last layer.
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关键词
siamese networks,algonauts challenge,neural activity,end-to-end
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