Advances in Metrology for Artificial Intelligence and Neural Network Applications
A special issue of Metrology (ISSN 2673-8244).
Deadline for manuscript submissions: 25 June 2026 | Viewed by 187
Special Issue Editors
Interests: impedance measurements; impedance spectroscopy; sine-fitting algorithms; automatic measurement systems; power quality monitoring/measurements; non-destructive electronic measurement systems; metrology; uncertainty and metrology for AI
Special Issues, Collections and Topics in MDPI journals
Interests: metrology and measurements; metrological characaterization of human–machine interfaces; cyber–physical systems for measurements; AI for biomedical applications; brain–computer interfaces; microwave reflectometry; biosensors
Special Issues, Collections and Topics in MDPI journals
Interests: electronic measurements for superconducting magnets and cables; brain–computer interfaces; transfer learning algorithms; anomaly detection; embedded AI; hardware cybersecurity
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue of Metrology, “Advances in Metrology for Artificial Intelligence and Neural Network Applications”, focuses on the emerging intersection between measurement science and intelligent computational systems. Artificial intelligence (AI) and neural networks are becoming integral to research, industry, and manufacturing, and it is thus essential to facilitate the metrological characterization of data-driven models.
We seek contributions that address novel metrological methods and frameworks tailored for AI applications, exploring, for example, measurement uncertainty in data acquisition, model validation, and explainability. Topics of interest include the design of metrological infrastructures for AI-based systems, the calibration of sensors/measurement devices enhanced by machine learning, and the role of uncertainty quantification in neural network performance evaluation. Emphasis is also placed on digital metrology and data integrity, fostering cross-disciplinary contributions between metrologists and AI developers. By advancing the metrological foundation of AI technologies, this Special Issue aims to promote transparency, reproducibility, and eventual standardization across data-driven domains, contributing to the development of robust AI-based intelligent measurement systems.
Dr. Pedro M. Ramos
Dr. Egidio De Benedetto
Dr. Antonio Esposito
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 250 words) can be sent to the Editorial Office for assessment.
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. Metrology is an international peer-reviewed open access quarterly 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 1200 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
- metrology
- artificial intelligence
- neural networks
- measurement uncertainty
- data quality
- digital metrology
- machine learning
- model validation
- traceability
- uncertainty quantification
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
