A Digitization and Conversion Tool for Imaged Drawings to Intelligent Piping and Instrumentation Diagrams (P&ID)
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- Dong-Han Kang & So-Won Choi & Eul-Bum Lee & Sung-O Kang, 2024. "Auto-Routing Systems (ARSs) with 3D Piping for Sustainable Plant Projects Based on Artificial Intelligence (AI) and Digitalization of 2D Drawings and Specifications," Sustainability, MDPI, vol. 16(7), pages 1-38, March.
- Min-Ji Park & Eul-Bum Lee & Seung-Yeab Lee & Jong-Hyun Kim, 2021. "A Digitalized Design Risk Analysis Tool with Machine-Learning Algorithm for EPC Contractor’s Technical Specifications Assessment on Bidding," Energies, MDPI, vol. 14(18), pages 1-31, September.
- So-Won Choi & Eul-Bum Lee & Jong-Hyun Kim, 2021. "The Engineering Machine-Learning Automation Platform ( EMAP ): A Big-Data-Driven AI Tool for Contractors’ Sustainable Management Solutions for Plant Projects," Sustainability, MDPI, vol. 13(18), pages 1-33, September.
- Su Jin Choi & So Won Choi & Jong Hyun Kim & Eul-Bum Lee, 2021. "AI and Text-Mining Applications for Analyzing Contractor’s Risk in Invitation to Bid (ITB) and Contracts for Engineering Procurement and Construction (EPC) Projects," Energies, MDPI, vol. 14(15), pages 1-28, July.
- Eun-Seop Yu & Jae-Min Cha & Taekyong Lee & Jinil Kim & Duhwan Mun, 2019. "Features Recognition from Piping and Instrumentation Diagrams in Image Format Using a Deep Learning Network," Energies, MDPI, vol. 12(23), pages 1-19, November.
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Keywords
imaged drawing; piping and instrumentation diagram (P&ID); digitized engineering drawing; template matching; artificial intelligence (AI); optical character recognition (OCR); optical symbol recognition;All these keywords.
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