Direct: Deep Discriminative Embedding for Clustering of Ligo Data
Direct: Deep Discriminative Embedding for Clustering of Ligo Data
In this paper, benefiting from the strong ability of deep neural network in estimating non-linear functions, we propose a discriminative embedding function to be used as a feature extractor for clustering tasks. The trained embedding function transfers knowledge from the domain of a labeled set of morphologically-distinct images, known as …