I have the network architecture from the paper learning fine-grained image similarity with deep ranking and I am unable to figure out how the output from the three parallel network is merged using the linear embedding layer,The only information given on this layer, in the paper isFinally, we normalize the embeddings from the three parts, and combine them with a linear embedding layer. In this paper, The dimension of the embedding is 4096.Can anyone help me figuring out what exactly is this layer , the author is talking about?
Unable to figure out the linear embedding layer in the convolutional neural network?
neural network