Journal Menu► ▼ Journal Menu
Journal Browser► ▼ Journal Browser
Special Issue "Recent Advances in Synthetic Data Generation"
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 18548
Special Issue Editors
2. Biodonostia Health Research Institute, eHealth Group, Paseo Doctor Begiristain, s/n, 20014 San Sebastián, Spain
Interests: health; software; data; network; data preparation; QoD; Synthetic data generation for data security / privacy
Interests: patient rehabilitation; virtual reality; artificial intelligence; computer games
Special Issue Information
Scientific and technological advances in recent decades have led to the digitization and increased generation and collection of data describing real-world applications or processes. In addition, machine learning models and artificial intelligence applications built on data have been proven to improve management and decision making about these applications and processes.
Despite the potential of data-based solutions, there are many issues that prevent or delay the development of such solutions. The most notable issues are the access to data, and the captured sample’s representativeness of the real population. Access to real data can be delayed or even prevented for various reasons such as privacy, security and intellectual property, or required (quality) capturing and preparation technology development. Sample representativeness is another critical issue that relates to class imbalance and representation of rare and extreme events, which is critical for ML model performance.
Synthetic data (SD) is described in this context as “any production data applicable to a given situation that are not obtained by direct measurement”. SD has three key use cases: (i) data augmentation: to balance datasets or supplement available data before training an ML model; (ii) privacy-preservation: to allow safe and private sharing of sensitive data; (iii) simulation: estimating and teaching systems in situations that haven’t been observed in actual reality.
The need for a comprehensive solution to exploit developments in Big Data and AI technology has never been greater, and synthetic data generation (SDG) research has been underway for some time with promising results in various application areas, including healthcare, cybersecurity, industrial processes, and energy consumption. Research has addressed the SDG of different data modalities (written natural language, images, video, tabular data, time series data, etc.) using different technological approaches.
The main objective of this Special Issue is to bring together diverse, novel and impactful research on synthetic data generation, thereby accelerating research in this field and the adoption of these techniques for real-world applications.
Contributions from different application domains, use cases and data modalities are sought by this Special Issue.
Submissions should be of high enough quality for an international journal and should not be submitted or published elsewhere. However, the extended versions of conference papers that show significant improvement (minimum of over 30%) can be considered for review in this Special Issue. In addition, we welcome review papers covering the subjects of this Special Issue.
Technical Program Committee Members:
- Dr. Debbie Rankin - Ulster University
- Dr. Ane Alberdi – Mondragon Unibertsitatea
- Dr. Rodrigo Cilla – Vicomtech - BRTA
Dr. Gorka Epelde Unanue
Dr. Darryl Charles
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. Electronics 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 2000 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.
- Synthetic data generation
- Generative adversarial networks
- Privacy preserving data
- Data augmentation
- Artificial intelligence
- Imbalanced learning