Results 121 to 130 of about 237,311 (276)

Piezoelectric Origami Metamaterials for Enhanced Handwriting Recognition and Trajectory Tracking

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study introduces origami metamaterials inspired by Kresling piezoelectric generators to enhance biometric authentication and handwriting trajectory recognition. Overcoming sensor limitations in conventional devices, the design enables multichannel data acquisition with fewer sensors, utilizing machine learning to accurately identify content ...
Yinzhi Jin, Ting Tan, Zhimiao Yan
wiley   +1 more source

Highly Efficient Classification of Time‐Series Based on Resistive Switching Cluster‐Assembled Materials

open access: yesAdvanced Intelligent Systems, EarlyView.
Cluster‐assembled nanocomposite devices are employed for the classification of neuronal traces, without any preprocessing of the input time‐series or prior training of the nonlinear devices. The classification method relies on the statistical analysis of the device's output time‐series, achieving higher classification accuracy compared to more energy ...
Filippo Profumo   +5 more
wiley   +1 more source

Internet of things (IoT) for smart agriculture: Assembling and assessment of a low-cost IoT system for polytunnels. [PDF]

open access: yesPLoS One, 2023
Jaliyagoda N   +6 more
europepmc   +1 more source

IEEE Access Special Section Editorial: The Plethora of Research in Internet of Things (IoT)

open access: gold, 2016
Abderrezak Rachedi   +3 more
openalex   +1 more source

Optoelectronic Neuromorphic System Based on Amorphous Indium–Gallium–Zinc–Oxide Thin‐Film Transistor for Spiking Neural Networks

open access: yesAdvanced Intelligent Systems, EarlyView.
An amorphous indium–gallium–zinc–oxide (IGZO)‐based optoelectronic neuromorphic system integrating light guides is introduced. The IGZO‐based optoelectronic synaptic transistor demonstrates high retention through a negative gate bias and emulates synaptic plasticity.
Yumin Yun   +6 more
wiley   +1 more source

Machine learning for Internet of Things (IoT) device identification: a comparative study. [PDF]

open access: yesPeerJ Comput Sci
Tahaei H   +7 more
europepmc   +1 more source

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