  During the past decade breakthroughs in GPU hardware and deep neural networks
technologies have revolutionized the field of computer vision, making image
analytical potentials accessible to a range of real-world applications.
Technology Assisted Review (TAR) in electronic discovery though traditionally
has dominantly dealt with textual content, is witnessing a rising need to
incorporate multimedia content in the scope. We have developed innovative image
analytics applications for TAR in the past years, such as image classification,
image clustering, and object detection, etc. In this paper, we discuss the use
of image clustering applications to facilitate TAR based on our experiences in
serving clients. We describe our general workflow on leveraging image
clustering in tasks and use statistics from real projects to showcase the
effectiveness of using image clustering in TAR. We also summarize lessons
learned and best practices on using image clustering in TAR.
