TinyML

A pretrained teacher-guided low-fidelity framework, TGL-NSGA-II, achieved measured Kendall-τ values of 0.74 on keyword spotting and 0.62 on bird-call classification, exceeding predicted lower bounds o…

An INT8 quantization experiment on a TinyML ECG arrhythmia detection model cut its size from 87.5 KB in FP32 to 34.6 KB, a roughly 60% reduction, while reported accuracy held at 93.8%, according to th…

A University of Wollongong researcher has developed a TinyML-powered device that detects disease-carrying mosquitoes by their wing-beat buzz with 88.3% accuracy, aiming to reduce the 700,000 annual de…

Researchers introduced D2H-AD, a hybrid anomaly detection framework using Hyperdimensional Computing that outperforms five baselines including One-Class SVM and Autoencoders across benchmark datasets.…