Advancing Transparency and Privacy: Explainable AI and Synthetic Data in Biometrics and Computer Vision Call for Papers

*** Call for Papers -  Image and Vision Computing***

Special issue on 
Advancing Transparency and Privacy: Explainable AI and Synthetic Data in Biometrics and Computer Vision

*PAPER SUBMISSION DEADLINE: Feb 7, 2025*
========================================


= OVERVIEW =

The rapid advancement of deep learning presents significant
challenges, particularly in the realm of ethical data collection and
usage. As regulations like the General Data Protection Regulation
(GDPR) gain prominence, the need for rigorous ethical standards across
various fields becomes increasingly apparent. In domains such as
biometrics, data has frequently been collected without appropriate
consent or ethical consideration. The medical field, in particular,
grapples with the dual challenges of safeguarding privacy and the
inherent difficulties of data acquisition.

Ensuring continued progress in deep learning requires that data
collection and generation practices adhere to strict ethical
guidelines. Greater control over data is essential to enhancing
transparency and fairness within deep learning
methodologies. Attention must also be given to the explainability of
systems trained on generated data, as well as the fairness
implications of using synthetic datasets. Addressing these challenges
is critical to fostering more ethical and responsible advancements in
deep learning.


= SPECIAL ISSUE TOPICS =

The Special Issue aims to promote research on the use of Explainable
AI and Synthetic Data to enhance transparency and privacy in
Biometrics and Computer Vision.  Topics include, but are certainly not
limited to:

    Responsible image synthesis
    Generative models
    Assessing and comparing AI explanations
    Researching causal learning and inference
    Synthetic medical data with clinical information
    Innovative synthesis of biometric data
    Generating natural language for explanations
    AI transparency and fairness
    Learning from synthetic data
    Interpreting biometric models and vulnerabilities
    Fairness enhancement with synthetic data



= IMPORTANT DATES =

Submission dates:

Submission Open Date: Oct 1, 2024
Final Manuscript Submission Deadline: Feb 7, 2025
Editorial Acceptance Deadline: Apr 7, 2025


= GUEST EDITORS =

Lucia Cascone - University of Salerno, Italy (lcascone@unisa.it)
Zilong Huang - TikTok, Singapore (zilonghuang2020@gmail.com)
Pedro C. Neto - Unilabs & FEUP (pedro.d.carneiro@inesctec.pt)
Ana F. Sequeira - INESC TEC (ana.f.sequeira@inesctec.pt)


= SUBMISSION AND REVIEW DETAILS =

Manuscript submission information:

The Journal's submission system (Editorial Manager) will be open for
submissions to our Special Issue from Oct 1st, 2024. Please refer to
the Guide for Authors to prepare your manuscript and select the
article type of “VSI: XAISynData” when submitting your
manuscript online. Both the Guide for Authors and the submission
portal could be found on the Journal Homepage: Guide for authors -

Image and Vision Computing - ISSN 0262-8856 (elsevier.com).
hhttps://www.elsevier.com/journals/image-and-vision-computing/0262-8856/guide-for-authors
https://www.elsevier.com/journals/image-and-vision-computing/0262-8856/guide-for-authors