Machine learning based automated evaluation of piping design

Abstract

The contributions of the co-authors are as follows: • Under supervision and guidance from the three co-authors, I collected data and created the dataset, developed the methodology, implemented the idea and wrote the paper. • Professor Chen I-Ming provided guidance on the use of deep learning in automation, pointed out the difference compared to deep learning related research in the domain of computer vision and highlighted the need to go beyond a binary classification. He also reviewed and provided constructive comments to various versions of the paper. • Dr. Dimitrios Pantazis was involved extensively in various discussions on the problem and an important improvement of the idea came up in a discussion with him. • Assistant Professor Sinno Jialin Pan provided guidance as an expert on deep and transfer learning, validated the approach theoretically and practically, reviewed and edited various versions of the paper.