As an extension to our neural network feature extraction (#5), we could do a high-throughput HTCondor run to extract basic image properties like:
entropy per channel
total intensity per channel
Then once we have the clustering in #5, we could see whether any of those are strongly associated with cluster membership. The overall goal is still to identify any obvious image attributes (e.g. empty images) that split the images into the two major clusters.
As an extension to our neural network feature extraction (#5), we could do a high-throughput HTCondor run to extract basic image properties like:
Then once we have the clustering in #5, we could see whether any of those are strongly associated with cluster membership. The overall goal is still to identify any obvious image attributes (e.g. empty images) that split the images into the two major clusters.