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Interactive Machine Learning tool with Automatic Tagging for Video Recognition System

Interactive machine learning (IML) is proposedto train intelligent systems. This paper proposes a new approach to solve the feedback delay and low visibility problem of conventional IML handling large-scale data. The approach features high-speed feedback using an approximate nearest neighbor, process controllability by the user, and priority based visualization. The validity of the approach is shown by an experiment with a prototype using a video where the lighting changes.