Federated learning lets a UAV fleet train a shared GPS spoofing detector without raw receiver data leaving any aircraft, and several recent UAV-FL designs weight each client by the validation accuracy it reports about itself. We show this self-report is an exploitable attack lever: two compromised clients of ten that p...
Will Jedrzejczak, Cole Walther, D. Gill et al.· 0 citations
As deep learning continues to develop at a fast pace, the field of medical imaging has also seen significant changes due to new technologies making it possible to automatically analyse large amounts of complex image data with much greater accuracy and efficiency than ever before. In this chapter, we will describe and e...
Ch V. V. Ramana, S. K. Alla, M. Ratnaraju et al.· CRC Press eBooks· 0 citations
Additive Manufacturing (AM) has grown from a rapid-prototyping tool into a legitimate production technology, yet its broader industrial adoption continues to be constrained by process variability, stochastic defect formation, and the near-impossibility of mapping complex Process Structure Property (PSP) relationships t...
Sarvesh Deshpande, Sahas Walvekar, V. Tiwary et al.· Journal of Advanced Manufact...· 0 citations
The convergence of blockchain and federated learning (FL) will be immensely beneficial for the Internet of Vehicles (IoV) in addressing some of the major concerns such as data security, privacy, scalability, and real-time decision-making. IoV systems architecture inherently creates extensive sensitive data, which is su...
Training code of the six compared methods (FedAvg, FedAvgM, FedProx, FedNova, SCAFFOLD and FedHAD), experiment runners, raw per-seed results and telemetry, analysis scripts that reproduce every table and figure of the paper, and the pre-registrations of the control batteries. FedHAD derives each client's number of loca...
Tiago Miranda Linhares, Ahmed Patel, Marcial P. Fernández· Zenodo (CERN European Organi...· 0 citations
ABSTRACT The reliance on vocal communication services, particularly in environments where the security aspects are highly valued such as emergencies, call for reliable methods for that detect the manipulation of environmental sound. One of the current challenges is the detection of SceneFake audio where only the enviro...
Sakshi, Mohit Dua· Fire and Materials· 0 citations
In present times, the rise of electronic healthcare has made vast amounts of public health data available, including clinical health records, laboratory results, genomic datasets, and public health–monitoring data. These datasets give significant opportunities for artificial intelligence (AI) to strengthen healthcare b...
N. Suganya, P. Gouthami, M. Krishnamoorthi· CRC Press eBooks· 0 citations
The combination of artificial intelligence (AI) and precision medicine could potentially change the way medicine is practiced. In this scenario, advances in precision medicine technology will enable healthcare providers to identify the phenotype of each patient who has a unique β-cell response to treatment, as well as...
Deep learning has been a key component of recent advancements in medical image processing, but traditional centralized learning models raise serious questions about data privacy in health data. Federated Learning (FL) is a novel paradigm for training models across institutions without sharing any raw medical data. In t...
Mobile learning scenarios in adult education impose mutually constraining technical requirements regarding real‑time interaction performance, recommendation accuracy, and data privacy protection. Neither cloud‑centric centralized inference nor device‑only local com‑ putation can adequately satisfy these demands. In thi...
Lin Chen, Linping Han· International Journal of Int...· 0 citations
[1] N. J. Sarna, F. A. Rithen, U. S. Jui, S. Belal, Al Amin, T. K. Oishee, and A. K. M. Muzahidul Islam, “AI Driven Fraud Detection Models in Financial Networks: A Comprehensive Systematic Review,” IEEE Access, vol. 13, pp. 141204–141233, 2025, doi: 10.1109/ACCESS.2025.3596060. [2] A. A. Almazroi and N. Ayub, “Online P...
Nikita Vikas Chavan, Prof. S. S. Medhe, Dr. H. B. Jadhav· International Journal of Adv...· 0 citations
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
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