董 飛艶
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Integrating deep learning-based object detection and optical character recognition for automatic extraction of link information from piping and instrumentation diagrams
著者:
董 飛艶,陳 実,出町 和之,（東京大）,橋立 竜太,高屋 茂,（JAEA）
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Deep Learning Nuclear Power Plants (NPPs) Object Detection Optical Character Recognition (OCR) Piping and Instrumentation Diagrams (P&IDs)
董 飛艶,陳 実,出町 和之,（東京大）,橋立 竜太,高屋 茂,（JAEA）
発刊日:
公開日:
キーワードタグ:
Deep Learning Nuclear Power Plants (NPPs) Object Detection Optical Character Recognition (OCR) Piping and Instrumentation Diagrams (P&IDs)
Piping and Instrumentation Diagrams (P&IDs) contain information about the piping and process equipment together with the instrumentation and control devices, which is essential to the design and management of Nuclear Power Plants (NPPs). There are abundant complex objects on P&IDs, with imbalanced distribution of these objects and their linked information across different diagrams. The complexity of P&IDs thus is increased which make automatic identification difficult. Therefore, the content of P&IDs is gen...