All one needs to know about metaverse: A complete survey on technological singularity, virtual ecosystem, and research agenda

LH Lee, T Braud, PY Zhou, L Wang… - … and trends® in …, 2024 - nowpublishers.com
Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We
have created various computer-mediated virtual environments, including social networks …

Algorithmic fairness in artificial intelligence for medicine and healthcare

RJ Chen, JJ Wang, DFK Williamson, TY Chen… - Nature biomedical …, 2023 - nature.com
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …

Advances and open problems in federated learning

P Kairouz, HB McMahan, B Avent… - … and trends® in …, 2021 - nowpublishers.com
Federated learning (FL) is a machine learning setting where many clients (eg, mobile
devices or whole organizations) collaboratively train a model under the orchestration of a …

Federated learning: Challenges, methods, and future directions

T Li, AK Sahu, A Talwalkar… - IEEE signal processing …, 2020 - ieeexplore.ieee.org
Federated learning involves training statistical models over remote devices or siloed data
centers, such as mobile phones or hospitals, while kee** data localized. Training in …

Review on Convolutional Neural Networks (CNN) in vegetation remote sensing

T Kattenborn, J Leitloff, F Schiefer, S Hinz - ISPRS journal of …, 2021 - Elsevier
Identifying and characterizing vascular plants in time and space is required in various
disciplines, eg in forestry, conservation and agriculture. Remote sensing emerged as a key …

Federated learning for internet of things: A comprehensive survey

DC Nguyen, M Ding, PN Pathirana… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …

A survey on federated learning

C Zhang, Y **e, H Bai, B Yu, W Li, Y Gao - Knowledge-Based Systems, 2021 - Elsevier
Federated learning is a set-up in which multiple clients collaborate to solve machine
learning problems, which is under the coordination of a central aggregator. This setting also …

Federated learning for smart healthcare: A survey

DC Nguyen, QV Pham, PN Pathirana, M Ding… - ACM Computing …, 2022 - dl.acm.org
Recent advances in communication technologies and the Internet-of-Medical-Things (IOMT)
have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI …

A survey on security and privacy of federated learning

V Mothukuri, RM Parizi, S Pouriyeh, Y Huang… - Future Generation …, 2021 - Elsevier
Federated learning (FL) is a new breed of Artificial Intelligence (AI) that builds upon
decentralized data and training that brings learning to the edge or directly on-device. FL is a …

Federated optimization in heterogeneous networks

T Li, AK Sahu, M Zaheer, M Sanjabi… - … of Machine learning …, 2020 - proceedings.mlsys.org
Federated Learning is a distributed learning paradigm with two key challenges that
differentiate it from traditional distributed optimization:(1) significant variability in terms of the …