SYSTEM AND METHOD FOR INTERACTIVE REPRESENTATION LEARNING TRANSFER THROUGH DEEP LEARNING OF FEATURE ONTOLOGIES

摘要

A method for interactive representation learning transfer to a convolutional neural network (CNN) is presented. The method includes obtaining at least first and second input image datasets from first and second imaging modalities. Furthermore, the method includes performing at least one of jointly training a first supervised learning CNN based on labels associated with the first input image dataset and a second supervised learning CNN based on labels associated with the second input image dataset to generate one or more common feature primitives and corresponding mapping functions and jointly training a first unsupervised learning CNN and a second unsupervised learning CNN with the first and second input image dataset respectively to learn compressed representations of the input image datasets, including common feature primitives and corresponding mapping functions and storing the common feature primitives and the corresponding mapping functions in a feature primitive repository.