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In this digital transformation era, the demand for automatic pattern extraction from printed materials has never been higher, making it one of the most eminent problems nowadays. In this paper, we propose a solution for pattern recognition in highly complex technical drawings, which is then applied to solve the problem presented by the Toyota Project. By utilizing state-of-the-art models and proposing several improvements to the methods of both phases, our experiments on nearly five thousand real technical drawings show promising results and the capability to reduce manual labeling effort to a great extent.
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