Visual Understanding of Multiple Attributes Learning Model of X-Ray Scattering Images

Citation

Huang, X.; Jamonnak, S.; Zhao, Y.; Wang, B.; Nguyen, M.H.; Yager, K.G.; Xu, W. "Visual Understanding of Multiple Attributes Learning Model of X-Ray Scattering Images" International Conference on Computer Vision 2019, 2019 24.
doi:

Summary

We describe a visualization tool for x-ray scattering data.

Abstract

This extended abstract presents a visualization system, which is designed for domain scientists to visually understand their deep learning model of extracting multiple attributes in x-ray scattering images. The system focuses on studying the model behaviors related to multiple structural attributes. It allows users to explore the images in the feature space, the classification output of different attributes, with respect to the actual attributes labelled by domain scientists. Abundant interactions allow users to flexibly select instance images, their clusters, and compare them visually in details. Two preliminary case studies demonstrate its functionalities and usefulness.