Demonstration of MaskSearch: Efficiently Querying Image Masks for
  Machine Learning Workflows
Lindsey Linxi Wei Chung Yik Edward Yeung Hongjian Yu Jingchuan Zhou Dong He Magdalena Balazinska
We demonstrate MaskSearch, a system designed to accelerate queries over
databases of image masks generated by machine learning models. MaskSearch
formalizes and accelerates a new category of queries for retrieving images and
their corresponding masks based on mask properties, which support various
applications, from identifying spurious correlations learned by models to
exploring discrepancies between model saliency and human attention. This
demonstration makes the following contributions:(1) the introduction of
MaskSearch's graphical user interface (GUI), which enables interactive
exploration of image databases through mask properties, (2) hands-on
opportunities for users to explore MaskSearch's capabilities and constraints
within machine learning workflows, and (3) an opportunity for conference
attendees to understand how MaskSearch accelerates queries over image masks.