Toward trustworthy artificial intelligence (TAI) in the context of explainability and robustness
From the innovation, Artificial Intelligence (AI) materialized as one of the noticeable research
areas in various technologies and has almost expanded into every aspect of modern human …
areas in various technologies and has almost expanded into every aspect of modern human …
Unlocking the black box: an in-depth review on interpretability, explainability, and reliability in deep learning
Deep learning models have revolutionized numerous fields, yet their decision-making
processes often remain opaque, earning them the characterization of “black-box” models …
processes often remain opaque, earning them the characterization of “black-box” models …
Towards secure big data analysis via fully homomorphic encryption algorithms
Privacy-preserving techniques allow private information to be used without compromising
privacy. Most encryption algorithms, such as the Advanced Encryption Standard (AES) …
privacy. Most encryption algorithms, such as the Advanced Encryption Standard (AES) …
The role of explainable AI in the research field of AI ethics
H Vainio-Pekka, MOO Agbese, M Jantunen… - ACM Transactions on …, 2023 - dl.acm.org
Ethics of Artificial Intelligence (AI) is a growing research field that has emerged in response
to the challenges related to AI. Transparency poses a key challenge for implementing AI …
to the challenges related to AI. Transparency poses a key challenge for implementing AI …
3D face reconstruction: the road to forensics
3D face reconstruction algorithms from images and videos are applied to many fields, from
plastic surgery to the entertainment sector, thanks to their advantageous features. However …
plastic surgery to the entertainment sector, thanks to their advantageous features. However …
Towards learning trustworthily, automatically, and with guarantees on graphs: An overview
The increasing digitization and datification of all aspects of people's daily life, and the
consequent growth in the use of personal data, are increasingly challenging the current …
consequent growth in the use of personal data, are increasingly challenging the current …
A primer on the use of machine learning to distil knowledge from data in biological psychiatry
Applications of machine learning in the biomedical sciences are growing rapidly. This
growth has been spurred by diverse cross-institutional and interdisciplinary collaborations …
growth has been spurred by diverse cross-institutional and interdisciplinary collaborations …
[HTML][HTML] Recent Applications of Explainable AI (XAI): A Systematic Literature Review
M Saarela, V Podgorelec - Applied Sciences, 2024 - mdpi.com
This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …
Privacy meets explainability: A comprehensive impact benchmark
S Saifullah, D Mercier, A Lucieri, A Dengel… - ar** fair deep learning models for identity-sensitive applications (eg, face attribute
recognition) has gained increasing attention from the research community. Indeed, it has …
recognition) has gained increasing attention from the research community. Indeed, it has …