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This extended abstract presents a visualization system, which is designed fordomain scientists to visually understand their deep learning model ofextracting multiple attributes in x-ray scattering images. The system focuseson studying the model behaviors related to multiple structural attributes. Itallows users to explore the images in the feature space, the classificationoutput of different attributes, with respect to the actual attributes labelledby domain scientists. Abundant interactions allow users to flexibly selectinstance images, their clusters, and compare them visually in details. Twopreliminary case studies demonstrate its functionalities and usefulness.

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