Predicting population neural activity in the Algonauts challenge using end-to-end trained Siamese networks and group convolutions
arxiv(2020)
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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