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相关论文: Digitize-PID: Automatic Digitization of Piping and…

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One of the most common modes of representing engineering schematics are Piping and Instrumentation diagrams (P&IDs) that describe the layout of an engineering process flow along with the interconnected process equipment. Over the years,…

计算机视觉与模式识别 · 计算机科学 2019-02-01 Rohit Rahul , Shubham Paliwal , Monika Sharma , Lovekesh Vig

Piping and Instrumentation Diagrams (P&IDs) constitute the foundational blueprint of a plant, depicting the interconnections among process equipment, instrumentation for process control, and the flow of fluids and control signals. In their…

计算机视觉与模式识别 · 计算机科学 2025-05-20 Soumya Swarup Prusty , Astha Agarwal , Srinivasan Iyenger

Digitizing engineering diagrams like Piping and Instrumentation Diagrams (P&IDs) plays a vital role in maintainability and operational efficiency of process and hydraulic systems. Previous methods typically decompose the task into separate…

计算机视觉与模式识别 · 计算机科学 2025-12-22 Jan Marius Stürmer , Marius Graumann , Tobias Koch

Automating the digitization of Piping and Instrumentation Diagrams (P&IDs) into structured process graphs would unlock significant value in plant operations, yet progress is bottlenecked by a fundamental data problem: engineering drawings…

计算机视觉与模式识别 · 计算机科学 2026-04-21 Suraj Prasad , Pinak Mahapatra

Piping and Instrumentation Diagrams (P&ID) are ubiquitous in several manufacturing, oil and gas enterprises for representing engineering schematics and equipment layout. There is an urgent need to extract and digitize information from P&IDs…

计算机视觉与模式识别 · 计算机科学 2021-09-10 Shubham Paliwal , Monika Sharma , Lovekesh Vig

Developing Piping and Instrumentation Diagrams (P&IDs) is a crucial step during the development of chemical processes. Currently, this is a tedious, manual, and time-consuming task. We propose a novel, completely data-driven method for the…

计算与语言 · 计算机科学 2024-01-17 Edwin Hirtreiter , Lukas Schulze Balhorn , Artur M. Schweidtmann

A piping and instrumentation diagram (P&ID) is a central reference document in chemical process engineering. Currently, chemical engineers manually review P&IDs through visual inspection to find and rectify errors. However, engineering…

计算工程、金融与科学 · 计算机科学 2026-05-28 Lukas Schulze Balhorn , Niels Seijsener , Kevin Dao , Minji Kim , Dominik P. Goldstein , Ge H. M. Driessen , Artur M. Schweidtmann

Buildings directly and indirectly emit a large share of current CO2 emissions. There is a high potential for CO2 savings through modern control methods in building automation systems (BAS) like model predictive control (MPC). For a proper…

计算机视觉与模式识别 · 计算机科学 2021-09-01 Florian Stinner , Martin Wiecek , Marc Baranski , Alexander Kümpel , Dirk Müller

The traditional mode of recording faults in heavy factory equipment has been via hand marked inspection sheets, wherein a machine engineer manually marks the faulty machine regions on a paper outline of the machine. Over the years, millions…

计算机视觉与模式识别 · 计算机科学 2018-12-19 Rohit Rahul , Arindam Chowdhury , Animesh , Samarth Mittal , Lovekesh Vig

The Piping and Instrumentation Diagrams (P&IDs) are foundational to the design, construction, and operation of workflows in the engineering and process industries. However, their manual creation is often labor-intensive, error-prone, and…

机器学习 · 计算机科学 2024-12-18 Shreeyash Gowaikar , Srinivasan Iyengar , Sameer Segal , Shivkumar Kalyanaraman

The digitization of documents allows for wider accessibility and reproducibility. While automatic digitization of document layout and text content has been a long-standing focus of research, this problem in regard to graphical elements,…

计算机视觉与模式识别 · 计算机科学 2023-07-06 Omar Moured , Jiaming Zhang , Alina Roitberg , Thorsten Schwarz , Rainer Stiefelhagen

Recognizing symbols in architectural CAD drawings is critical for various advanced engineering applications. In this paper, we propose a novel CAD data annotation engine that leverages intrinsic attributes from systematically archived CAD…

Deep learning-based segmentation and classification are crucial to large-scale biomedical imaging, particularly for 3D data, where manual analysis is impractical. Although many methods exist, selecting suitable models and tuning parameters…

Aligning functional schematics with 2D and 3D scene acquisitions is crucial for building digital twins, especially for old industrial facilities that lack native digital models. Current manual alignment using images and LiDAR data does not…

计算机视觉与模式识别 · 计算机科学 2026-02-18 Flavien Armangeon , Thibaud Ehret , Enric Meinhardt-Llopis , Rafael Grompone von Gioi , Guillaume Thibault , Marc Petit , Gabriele Facciolo

Interaction is critical for data analysis and sensemaking. However, designing interactive physicalizations is challenging as it requires cross-disciplinary knowledge in visualization, fabrication, and electronics. Interactive…

Recent advances in generative AI have accelerated the discovery of novel chemicals and materials. However, scaling these discoveries to industrial production remains a major bottleneck due to the synthesis gap -- the need to develop…

机器学习 · 计算机科学 2025-08-19 Sakhinana Sagar Srinivas , Shivam Gupta , Venkataramana Runkana

We have developed MatGD (Material Graph Digitizer), which is a tool for digitizing a data line from scientific graphs. The algorithm behind the tool consists of four steps: (1) identifying graphs within subfigures, (2) separating axes and…

计算机视觉与模式识别 · 计算机科学 2023-11-23 Jaewoong Lee , Wonseok Lee , Jihan Kim

Quality control of assembly processes is essential in manufacturing to ensure not only the quality of individual components but also their proper integration into the final product. To assist in this matter, automated assembly control using…

计算机视觉与模式识别 · 计算机科学 2025-09-17 Jonas Werheid , Shengjie He , Aymen Gannouni , Anas Abdelrazeq , Robert H. Schmitt

The growing volume of digital images necessitates advanced systems for efficient categorization and retrieval, presenting a significant challenge in database management and information retrieval. This paper introduces PICS (Pipeline for…

计算机视觉与模式识别 · 计算机科学 2024-02-16 Grant Rosario , David Noever

In industrial manufacturing, deploying deep learning models for visual inspection is mostly hindered by the high and often intractable cost of collecting and annotating large-scale training datasets. While image synthesis from 3D CAD models…

计算机视觉与模式识别 · 计算机科学 2025-12-30 Nico Baumgart , Markus Lange-Hegermann , Mike Mücke
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