Results 131 to 140 of about 2,597 (210)

Deploying TinyML for energy-efficient object detection and communication in low-power edge AI systems. [PDF]

Sci Rep
Bhushan CM, Koppuravuri P, Prasanthi N, Gazi F, Hussain MM, Abdussami M, Devi AA, Faizi J.   +7 more
europepmc   +1 more source

Towards Contactless Elevators with TinyML using CNN-based Person Detection and Keyword Spotting

This study presents a proof of concept for a contactless elevator operation system aimed at minimizing human intervention while enhancing safety, intelligence, and efficiency.
Niture, Deeplaxmi V., Pimpalkar, Anway S.   +1 more
core  

FastKAN-DDD: A novel fast Kolmogorov-Arnold network-based approach for driver drowsiness detection optimized for TinyML deployment. [PDF]

PLoS One
Essahraui S, Lamaakal I, Maleh Y, El Makkaoui K, Bouami MF, Ouahbi I, Elmannai H, Abd El-Latif AA.   +7 more
europepmc   +1 more source

Secure edge-based IoMT framework for ICU monitoring with TinyML and post-quantum cryptography. [PDF]

Sci Rep
Khan UH, Qamar A, Khan R, Alturise F, Alshaabani AR, Alkhalaf S.   +5 more
europepmc   +1 more source

An Intelligent, low-cost water quality monitoring system with on-device machine learning and cloud integration. [PDF]

Sci Rep
Sharma S, Mishra D, Yadav A, Gami B, Madhan ES.   +4 more
europepmc   +1 more source

An optimized stacking-based TinyML model for attack detection in IoT networks. [PDF]

PLoS One
Sharma A, Rani S, Shabaz M.
europepmc   +1 more source

Intelligent Classification of Urban Noise Sources Using TinyML: Towards Efficient Noise Management in Smart Cities. [PDF]

Sensors (Basel)
Remolina Soto MS, Amaya Guzmán B, Aya-Parra PA, Perdomo OJ, Becerra-Fernandez M, Sarmiento-Rojas J.   +5 more
europepmc   +1 more source

Real-time on-device weed identification using a hardware-efficient lightweight CNN. [PDF]

Front Plant Sci
Zhang Y, Lu Y, Martinez-Rau LS, Qiu Q, Bader S.   +4 more
europepmc   +1 more source

MicroHD: An Accuracy-Driven Optimization of Hyperdimensional Computing Algorithms for TinyML systems

Hyperdimensional computing (HDC) is emerging as a promising AI approach that can effectively target TinyML applications thanks to its lightweight computing and memory requirements. Previous works on HDC showed that limiting the standard 10k dimensions of
Ponzina, Flavio, Rosing, Tajana
core  

Development of a bench system with capacitive sensor, sample compression, and TinyML for iron ore moisture measurement. [PDF]

Sci Rep
Pinto ÉS, Matos SN, Neiva M, Santos GA, Marcolino LS, Ueyama J, Euzébio TAM, Pessin G, Pritzelwitz PV, Segundo AKR.   +9 more
europepmc   +1 more source