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Industry PhD student at Sony and LTH. Funded in the WASP initiative.
The project is starting in computer vision and image analysis to become familiar with current methods and a well established domain. This is used as an arena to find a machine task that involves human interaction and a non-static environment that allows incremental learning. Designing the task and learning process to benefit from transparency of the agent decisions (explainability) is a secondary goal.
While deep learning with large amounts of up-front learning data has made recent success, an agent that is able to learn incrementally from data available during usage should be more versatile. A human-in-the-loop approach, where the user is taking an active part in the learning or acting process, could be one way to give transparency but the human should not become a bottle-neck with no added value.
Working for Sony Europe in Lund and has been involved in different aspects of software development for mobile phones since 2001.
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