Special Issue "Explainable Artificial Intelligence for Biometrics 2021"
A special issue of Computers (ISSN 2073-431X).
Deadline for manuscript submissions: 15 August 2021.
Interests: machine learning; computer vision; biometrics; explainable AI; cryptography; mathematics education
Special Issues and Collections in MDPI journals
The "Workshop on Explainable & Interpretable Artificial Intelligence for Biometrics"—xAI4Biometrics Workshop—is embraced by the WACV 2021 Conference (http://wacv2021.thecvf.com/home). This workshop will be held on January 5, 2021, as a Fully Virtual Event. For more information about the workshop, please use the following link: http://vcmi.inesctec.pt/xai4biom_wacv/index.html.
Selected papers among the works presented at the workshop will be invited to submit extended versions to this Special Issue of Computers. The invited papers will be free of charge if they are accepted after peer review. The submission papers to the SI should be extended from the original workshop paper to the length of regular research or review articles, with at least 50% coverage of new results. All submitted papers will undergo our standard peer-review procedure. Accepted papers will be published in open access format in Computers and collected together in this Special Issue. There are no page limitations for this journal.
We are also inviting original research work focused on biometrics and promoting the development of a) methods to interpret the biometric models to validate their decisions, as well as to improve the models and detect possible vulnerabilities; b) quantitative methods to objectively assess and compare different explanations of the automatic decisions; c) methods to generate better explanations; and d) more transparent algorithms.
The main topics include, but are not limited to, the following:
- Methods to interpret the biometric models to validate their decisions as well as to improve the models and to detect possible vulnerabilities;
- Quantitative methods to objectively assess and compare different explanations of the automatic decisions;
- Methods and metrics to study/evaluate the quality of explanations obtained by post-model approaches and improve the explanations;
- Methods to generate model-agnostic explanations;
- Transparency and fairness in AI algorithms avoiding bias;
- Interpretable methods able to explain decisions of previously built and unconstrained (black box) models;
- Inherently interpretable (white box) models;
- Methods that use post-model explanations to improve the models’ training;
- Methods to achieve/design inherently interpretable algorithms (rule-based, case-based reasoning, regularization methods);
- Study on causal learning, causal discovery, causal reasoning, causal explanations, and causal inference;
- Natural Language generation for explanatory models;
- Methods for adversarial attacks detection, explanation and defense (“How can we interpret adversarial examples?”);
- Theoretical approaches of explainability (“What makes a good explanation?”);
- Applications of all the above including proof0of-concepts and demonstrators of how to integrate explainable AI into real-world work-flows and industrial processes;
- Novel theories, innovative methods, and meaningful applications that can potentially lead to significant advances in artificial neural networks in pattern recognition.
Dr. Ana Filipa Sequeira
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 papers will be 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. Computers is an international peer-reviewed open access monthly 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 1400 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.
- AI Explainability and Interpretability
- Machine Learning
- Computer Vision