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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Digitization of chemical process flow diagrams using deep convolutional neural networks
Maximilian F. Theisen, Kenji Nishizaki Flores, Lukas Schulze Balhorn, et al.
Digital Chemical Engineering (2022) Vol. 6, pp. 100072-100072
Open Access | Times Cited: 25

Showing 25 citing articles:

Energy transition technology comes with new process safety challenges and risks
Hans J. Pasman, Edison Sripaul, Faisal Khan, et al.
Process Safety and Environmental Protection (2023) Vol. 177, pp. 765-794
Open Access | Times Cited: 40
Learning from flowsheets: A generative transformer model for autocompletion of flowsheets
Gabriel Vogel, Lukas Schulze Balhorn, Artur M. Schweidtmann
Computers & Chemical Engineering (2023) Vol. 171, pp. 108162-108162
Open Access | Times Cited: 35
Digitize-HCD: A Dataset for Digitization of Handwritten Circuit Diagrams
Nadim Ahmed, Mirza Fuad Adnan, Ahmad Shafiullah, et al.
Data in Brief (2025) Vol. 59, pp. 111315-111315
Open Access
Revolutionizing Engineering and Construction Projects: The Role of Artificial Intelligence in Cost Estimation and Procurement
Римма Джусупова, Vasil Shteriyanov, Jan Bosch, et al.
(2025)
Closed Access
Toward automatic generation of control structures for process flow diagrams with large language models
Edwin Hirtreiter, Lukas Schulze Balhorn, Artur M. Schweidtmann
AIChE Journal (2023) Vol. 70, Iss. 1
Open Access | Times Cited: 12
Auto-Routing Systems (ARSs) with 3D Piping for Sustainable Plant Projects Based on Artificial Intelligence (AI) and Digitalization of 2D Drawings and Specifications
Donghan Kang, So-Won Choi, Eul‐Bum Lee, et al.
Sustainability (2024) Vol. 16, Iss. 7, pp. 2770-2770
Open Access | Times Cited: 2
A review of deep learning methods for digitisation of complex documents and engineering diagrams
Laura Jamieson, Carlos Francisco Moreno‐García, Eyad Elyan
Artificial Intelligence Review (2024) Vol. 57, Iss. 6
Open Access | Times Cited: 2
Artificial intelligence and machine learning at various stages and scales of process systems engineering
Karthik K. Srinivasan, Anjana Puliyanda, Devavrat Thosar, et al.
The Canadian Journal of Chemical Engineering (2024) Vol. 103, Iss. 3, pp. 1004-1035
Open Access | Times Cited: 2
A Symbol Recognition System for Single-Line Diagrams Developed Using a Deep-Learning Approach
Hina Bhanbhro, Yew Kwang Hooi, Worapan Kusakunniran, et al.
Applied Sciences (2023) Vol. 13, Iss. 15, pp. 8816-8816
Open Access | Times Cited: 6
Classification of Functional Types of Lines in P&IDs Using a Graph Neural Network
Gwangsik Kim, Byung Chul Kim
IEEE Access (2023) Vol. 11, pp. 73680-73687
Open Access | Times Cited: 5
Practical Software Development: Leveraging AI for Precise Cost Estimation in Lump-Sum EPC Projects
Римма Джусупова, Mina Ya-alimadad, Vasil Shteriyanov, et al.
2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) (2024), pp. 1023-1033
Closed Access | Times Cited: 1
Editorial: Special issue on emerging stars in digital chemical engineering
Jin Xuan, Jinfeng Liu
Digital Chemical Engineering (2024) Vol. 11, pp. 100148-100148
Open Access
Symbol Detection in Mechanical Engineering Sketches: Experimental Study on Principle Sketches with Synthetic Data Generation and Deep Learning
Sebastian Bickel, Stefan Goetz, Sandro Wartzack
Applied Sciences (2024) Vol. 14, Iss. 14, pp. 6106-6106
Open Access
Towards fully automated processing and analysis of construction diagrams: AI-powered symbol detection
Laura Jamieson, Carlos Francisco Moreno‐García, Eyad Elyan
International Journal on Document Analysis and Recognition (IJDAR) (2024)
Open Access
A method for the automated digitalization of fluid circuit diagrams
Valentin Stegmaier, Nasser Jazdi, Michael Weyrich
Computers in Industry (2024) Vol. 162, pp. 104139-104139
Open Access
Estimation of Processing Times and Economic Feasibility of Producing Moringa oleifera Lam. Capsules in Mexico
Elizabeth Delfín-Portela, Roberto Ángel Meléndez Armenta, María Eloísa Gurruchaga-Rodríguez, et al.
Applied Sciences (2024) Vol. 14, Iss. 16, pp. 7225-7225
Open Access
Engineering Data Funnel (WIP) – An Ontology-Enhanced LLM-Based Agent and MoE System for Engineering Data Processing
Nicolai Schoch, Mario Hoernicke, Nika Strem, et al.
2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA) (2024) Vol. 30, pp. 1-5
Closed Access
Estimation of Processing Times and Economic Feasibility to Produce Moringa Oleifera Lam. Capsules in Mexico.
Elizabeth Delfín-Portela, Roberto Ángel Meléndez-Armenta, María Eloísa Gurruchaga-Rodríguez, et al.
(2024)
Open Access
Revolutionizing Engineering and Construction Projects: The Role of Artificial Intelligence in Cost Estimation and Procurement
Римма Джусупова, Vasil Shteriyanov, Jan Bosch, et al.
(2024)
Closed Access
Mining Chemical Process Information from Literature for Generative Process Design: A Perspective
Artur M. Schweidtmann
Systems & control transactions. (2024) Vol. 3, pp. 84-91
Closed Access
From Then to Now and Beyond: Exploring How Machine Learning Shapes Process Design Problems
Burcu Beykal
Systems & control transactions. (2024) Vol. 3, pp. 16-21
Closed Access
Few-Shot Symbol Detection in Engineering Drawings
Laura Jamieson, Eyad Elyan, Carlos Francisco Moreno‐García
Applied Artificial Intelligence (2024) Vol. 38, Iss. 1
Open Access
Advancing P&ID Digitization with YOLOv5
Shreya M Gajbhiye, S R Bhamre, L N Teja Tadepalli, et al.
(2023), pp. 1-6
Closed Access | Times Cited: 1
Data augmentation for machine learning of chemical process flowsheets
Lukas Schulze Balhorn, Edwin Hirtreiter, Lynn Luderer, et al.
arXiv (Cornell University) (2023)
Open Access
Data augmentation for machine learning of chemical process flowsheets
Lukas Schulze Balhorn, Edwin Hirtreiter, Lynn Luderer, et al.
Computer-aided chemical engineering/Computer aided chemical engineering (2023), pp. 2011-2016
Open Access
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