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Across industries, many engineering documents and drawings have accumulated over the past few decades. However, they are mostly archived in paper or rudimentary electronic form (typically in an image or PDF format), rendering information retrieval highly inconvenient. As such, a lot of valuable engineering data have been left unutilized or at very least, difficult to access. Unfortunately, the existing open source tools do not offer a simple remedy. With this in mind, the proposed project aims to develop a systematic approach based on machine learning techniques for the digitalization of engineering specifications and documents.
Jun Chen
Qiqi Wang
Engineering - computer / electrical
Information and communications technologies
Accelerate
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