An Automated Engineering Assistant: Learning Parsers for Technical
  Drawings
  From a set of technical drawings and expert knowledge, we automatically learn
a parser to interpret such a drawing. This enables automatic reasoning and
learning on top of a large database of technical drawings. In this work, we
develop a similarity based search algorithm to help engineers and designers
find or complete designs more easily and flexibly. This is part of an ongoing
effort to build an automated engineering assistant. The proposed methods make
use of both neural methods to learn to interpret images, and symbolic methods
to learn to interpret the structure in the technical drawing and incorporate
expert knowledge.
