Results 71 to 80 of about 7,108,814 (163)

High Accuracy of Epileptic Seizure Detection Using Tiny Machine Learning Technology for Implantable Closed-Loop Neurostimulation Systems

BioMedInformatics
Background: Epilepsy is one of the most common and devastating neurological disorders, manifesting with seizures and affecting approximately 1–2% of the world’s population.
Evangelia Tsakanika, Vasileios Tsoukas, Athanasios Kakarountas, Vasileios Kokkinos   +3 more
doaj   +1 more source

Unveiling the Potential of Tiny Machine Learning for Enhanced People Counting in UWB Radar Data [PDF]

Tiny Machine Learning (TinyML) allows to move the intelligence processing as close as possible to where data are generated, hence reducing the latency with which a decision is made and being able to process data even when remote connection is scarce or ...
Roveri, Manuel, Pavan, Massimo, Caltabiano, Armando, Navarro, Luis González   +3 more
core   +1 more source

Tiny Neural Receiver: Enabling On-Device Learning for Scalable and Adaptive 6G Devices

AI
The evolution toward 6G communications requires integrating Tiny Machine Learning (TinyML) principles to enable intelligent, energy-efficient, and adaptable signal processing at the network edge. However, current receiver architectures face a fundamental
Iñigo Bilbao, Eneko Iradier, Jon Montalban, Marta Fernández, Iñaki Eizmendi, Pablo Angueira   +5 more
doaj   +1 more source

Gas Leakage Detection Using Tiny Machine Learning [PDF]

Gas leakage detection is a critical concern in both industrial and residential settings, where real-time systems are essential for quickly identifying potential hazards and preventing dangerous incidents.
Talei, H., Hanae Talei, Miloud Bagaa, El Barkani, M., Bagaa, M., Nabil Benamar, Benamar, N., Majda El Barkani   +7 more
core   +1 more source

An Evolving Multivariate Time Series Compression Algorithm for IoT Applications

Sensors
The Internet of Things (IoT) is transforming how devices interact and share data, especially in areas like vehicle monitoring. However, transmitting large volumes of real-time data can result in high latency and substantial energy consumption.
Hagi Costa, Marianne Silva, Ignacio Sánchez-Gendriz, Carlos M. D. Viegas, Ivanovitch Silva   +4 more
doaj   +1 more source

Design of a Tiny Machine Learning system for UWB radar based multi-target detection

, 2022
Tiny Machine Learning (TinyML) is a novel field of research which consists on designing machine and deep learning models at a reduced size, enabling them to be executed on tiny devices such as Internet-of-Things units, edge devices or embedded systems ...
González Navarro, Luis
core  

Drone Detection Using Tiny Machine Learning

As Machine Learning (ML) technology advances, the devices and servers required to collect, process, and store data are becoming increasingly complex. Tiny Machine Learning (TinyML) addresses this challenge by enabling simple ML models to run on small ...
Mays, Eric
core   +1 more source

Development and evaluation of a TinyML-based sensor fusion system for medical waste classification on low-cost embedded devices

Medisains
Background: Medical waste management in resource-limited healthcare facilities remains dominated by manual segregation, which is error-prone and difficult to standardize.
Dini Afriani, Irfan Fadil
doaj   +1 more source

TinyML Algorithms for Big Data Management in Large-Scale IoT Systems

Future Internet
In the context of the Internet of Things (IoT), Tiny Machine Learning (TinyML) and Big Data, enhanced by Edge Artificial Intelligence, are essential for effectively managing the extensive data produced by numerous connected devices.
Aristeidis Karras, Anastasios Giannaros, Christos Karras, Leonidas Theodorakopoulos, Constantinos S. Mammassis, George A. Krimpas, Spyros Sioutas   +6 more
doaj   +1 more source

Effective and adaptive tiny machine learning

DOTTORATONegli ultimi anni, il Tiny Machine Learning (TinyML) e' emerso come il ramo della ricerca sul Machine Learning che studia l'esecuzione di modelli di Machine e Deep Learning (MDL) su dispositivi estremamente limitati in termini di memoria ...
Pavan, Massimo
core