Results 181 to 190 of about 26,647 (212)

Intrusion Detection in the Internet of Things: A Comprehensive Review of Techniques, Architectures, Datasets, and Emerging Trends. [PDF]

Sensors (Basel)
Komal A, Li S.
europepmc   +1 more source

MAPFL: Modular Adaptive Personalised Federated Learning From Visual Sentiment to Physical Activity

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Human‐centric sensing tasks such as visual sentiment analysis and smartphone‐based human activity recognition (HAR) exhibit strong client heterogeneity from feature, label, and concept shifts. Among these, concept shift—how individual users interpret and generate human‐centric signals—is particularly challenging yet underexplored in federated ...
Chang Liu, Yapeng Li, Zengmao Wang, Dewen Soh, Bo Du   +4 more
wiley   +1 more source

Cyborg-swarm cooperation and game via affective-based brain-machine interface. [PDF]

Natl Sci Rev
Chen Z, Zhang L, Chen G, Liu H, Wang Z, Zhao X, Guo S, Zhao T, Sun M, Liang W, Qin L, Zhang M, Liu L, Wang W.   +13 more
europepmc   +1 more source

RES‐AD: An AutoML‐Driven Robust Ensemble Framework for Real‐Time Anomaly Detection and Energy Forecasting in Smart Grids

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurate load forecasting and reliable anomaly detection are critical for the stable operation of modern smart grids (SGs), which increasingly rely on cyber‐connected infrastructures. However, the integration of smart metres and two‐way communication exposes SGs to data integrity attacks that can manipulate consumption measurements, degrade ...
Murad Ali Khan, Naeem Iqbal, Syed Shehryar Ali Naqvi, Muhammad Faseeh, Do‐Hyeun Kim   +4 more
wiley   +1 more source

Adaptive continual botnet detection with self-supervised prototypical networks and few-shot learning for evolving botnet detection. [PDF]

Front Artif Intell
Junar N, Arockiasamy K.
europepmc   +1 more source

Robust Multi‐Source Batch Normalisation for Test‐Time Batch Adaptation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Test‐Time Batch Adaptation (TTBA) aims to adapt a pre‐trained source model to small, unlabelled target batches at test time. The TTBA methods focus on adapting the pre‐trained model or the target data in a one‐to‐one alignment paradigm. However, these one‐to‐one alignment paradigms assume that the source domain may share the same knowledge ...
Xinlin Xiao, Xiangtao Zheng, Jianhua Tao, Xiaoqiang Lu   +3 more
wiley   +1 more source

Transfer learning for T-cell response prediction. [PDF]

BMC Bioinformatics
Stadelmaier J, Malone B, Eggeling R.
europepmc   +1 more source

Patient-Specific Spatio-Temporal False Data Injection Attack Detection for IoMT Using a Graph-GRU Digital Twin and Kalman Innovation Features. [PDF]

Bioengineering (Basel)
Alkhammash EH, Ghaleb FA, Saeed F, Qasem SN.   +3 more
europepmc   +1 more source

Efficient Automatic Design of a 2D TMD FET via Machine Learning-Assisted TCAD Simulation. [PDF]

Micromachines (Basel)
Shi N, Wei ZJ, Wu T.
europepmc   +1 more source