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Sensors & Methods in Digitisation of Complex Documents and Engineering Diagrams

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Industrial Sensors".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 316

Special Issue Editors

School of Computing, Robert Gordon University, Aberdeen AB10 7QB, UK
Interests: computer vision; 3D visualization; AI; supervised and unsupervised machine learning
Special Issues, Collections and Topics in MDPI journals
School of Computer, Robert Gordon University, Aberdeen AB10 7AQ, UK
Interests: pattern recognition; computer vision; machine learning; medical image analysis; data science; natural language processing; document image analysis; graph matching

Special Issue Information

Dear Colleagues,

Large volumes of un-digitised and paper-based documents are still very common across different domains. For example, engineering drawings are used in various industries, such as oil and gas, construction and other types of engineering. Automated reading and interpretation of these types of documents are essential for various applications, partly because of the urgent need to improve business practices such as inventory, asset management, risk analysis, safety checks and other applications, and also due to the recent advancements in machine vision and image understanding. A typical diagram often contains symbols belonging to various classes with minor variations. Another critical challenge is the class-imbalance problem, wherein some types of symbols largely dominate the data while others are hardly represented. In addition, symbols, annotation and text overlap on these diagrams, thus making the automated processing and analysis of such documents very challenging for the computer vision research community.

This Special Issue aims to present the latest original developments and challenges in the application of sensors in digitisation of complex documents and engineering diagrams. For instance, reading, processing and analysing engineering drawings and complex documents using computer-vision-based methods. We invite authors to submit original articles and reviews related to recent advances in processing and analysing engineering diagrams across various industries (e.g., mechanical, electric, etc.). We are particularly interested in new trends and challenges in this area, including but not limited to:

  • Detecting and localising symbols, lines and text in complex documents and engineering drawings;
  • Automatic separation and extraction of text and graphic elements from such documents;
  • Heuristic-based methods and deep-learning-based methods for digitising engineering diagrams;
  • The challenge of data annotation to enable object recognition for extracting graphic elements from complex documents;
  • Systems that are capable of reverting diagrams into an intelligent form or a digital twin, capturing the structural relations between the elements depicted;
  • End-to-end framework for extracting text, graphics and connectivity information from engineering diagrams;
  • Reviews that capture the latest development and challenges in this area;
  • Application-based papers in this area.

Prof. Dr. Eyad Elyan
Dr. Carlos Moreno-García
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensor fusion and data integration
  • computer vision
  • vision sensors
  • sensor applications
  • sensing techniques
  • artificial intelligence
  • pattern recognition
  • machine learning
  • deep learning
  • data science
  • document image analysis
  • graph matching
  • 3D visualization
  • text detection and recognition
  • digitisation
  • convolutional neural network

Published Papers

There is no accepted submissions to this special issue at this moment.
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