Results 71 to 80 of about 2,597 (210)
Nanozymes Integrated Biochips Toward Smart Detection System
Advanced Science, Volume 13, Issue 11, 23 February 2026.This review systematically outlines the integration of nanozymes, biochips, and artificial intelligence (AI) for intelligent biosensing. It details how their convergence enhances signal amplification, enables portable detection, and improves data interpretation.
Dongyu Chen +10 more
wiley +1 more source
Neural Architecture Search for Tiny Incremental On-Device Learning [PDF]
, 2023 LAUREA MAGISTRALEL'apprendimento incrementale on-device è un promettente campo di ricerca in TinyML. Consiste nella capacità dei modelli di adattarsi a nuovi dati senza dipendere costantemente dalla connettività cloud.
LACAVA, MARCO
core
Use of Automation Technologies and Data Mining in Speech Recognition for Autism
Brain and Behavior, Volume 16, Issue 2, February 2026.Pipeline analyzes clinical and naturalistic speech using LENA, wav2vec 2.0, and foundation‐model ASR (Whisper) to enable scalable ASD detection and severity estimation. Future work integrates benchmarking, privacy‐preserving collaboration (federated learning), and explainable, edge‐ready AI for clinically credible assessment and longitudinal monitoring.
Rongjie Mao, Yuncheng Zhu
wiley +1 more source
TinyML with Meta-Learning on Microcontrollers for Air Pollution Prediction
ProceedingsTiny machine learning (tinyML) involves the application of ML algorithms on resource-constrained devices such as microcontrollers. It is possible to improve tinyML performance by using a meta-learning approach.
I Nyoman Kusuma Wardana +2 more
doaj +1 more source
Food Science &Nutrition, Volume 14, Issue 2, February 2026.The graphical abstract depicts an integrated multimodal AI pipeline for real‐time food safety and quality across the farm‐to‐fork continuum, where heterogeneous sensing modalities including vision, spectroscopy, electronic nose volatiles, biosensing, and IoT/RFID generate complementary data streams that undergo dataset engineering through ...
Zhaojie Chen, Guangyu Zhang, Fan Zhang
wiley +1 more source
PRDTinyML: deep learning-based TinyML-based pedestrian detection model in autonomous vehicles for smart cities [PDF]
Detecting pedestrians and cars in smart cities is a major task for autonomous vehicles (AV) to prevent accidents. Occlusion, distortion, and multi-instance pictures make pedestrian and rider detection difficult.
Alajlan, Norah N. +2 more
core +2 more sources
Methods in Ecology and Evolution, Volume 17, Issue 2, Page 357-370, February 2026.Abstract Camera traps, combined with AI, have emerged to achieve automated, scalable biodiversity monitoring. However, passive infrared (PIR) sensors that typically trigger camera traps are poorly suited for detecting small, fast‐moving ectotherms such as insects. Insects comprise over half of all animal species and are key components of ecosystems and
Ross J. Gardiner +2 more
wiley +1 more source
IEEE AccessCuffless continuous noninvasive blood pressure (cNIBP) monitoring based on photoplethysmography (PPG) has enjoyed great success through a wealth of high-performing machine learning (ML) algorithms.
Nour Faris Ali +3 more
doaj +1 more source
Advanced Sensor Research, Volume 5, Issue 1, January 2026.This paper reviews the state of the art and recent developments in thin‐film biosensors for the detection of neurotransmitters, small molecules, and biomarkers within flexible, implantable bioelectronic systems. It covers the main sensing modalities, including electrochemical, plasmonic, acoustic, and magnetic, alongside their materials, transduction ...
Massimo Mariello
wiley +1 more source
SciThe integration of artificial intelligence into the Industrial Internet of Things (IIoT), supported by edge computing architectures, marks a new paradigm of intelligent automation.
Margarita Terziyska +3 more
doaj +1 more source