Results 101 to 110 of about 16,826 (269)
Drone Detection Using Tiny Machine Learning [PDF]
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
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ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.This article explores high‐entropy‐stabilized oxides (HEOs) as novel functional materials for addressing critical issues in lithium–sulfur (Li–S) batteries, including lithium polysulfide (LPS) shuttling, inadequate conductivity, and slow redox kinetics.
Hassan Raza +10 more
wiley +1 more source
Deep feature optimization for enhanced fish freshness assessment
Ecological InformaticsAssessing fish eye freshness is vital for ensuring food safety and minimizing economic losses in the seafood industry. However, traditional sensory evaluation methods remain subjective, time-consuming, and inconsistent.
Phi-Hung Hoang +3 more
doaj +1 more source
Organic Photodetectors and Sensors for Low‐Light and Infrared Applications
Electron, EarlyView.This mini review highlights recent advances in organic photodetectors and sensors for low‐light and infrared applications, emphasizing molecular design, device architectures, and interface engineering that improve charge transport, detectivity, speed, and spectral selectivity.
Swarup Biswas, Hyeok Kim
wiley +1 more source
SRAM based computing-in-memory for tiny machine learning [PDF]
This dissertation investigates the potential of Computing-In-Memory (CIM) using Static Random-Access Memory (SRAM) to address the limitations of the Von Neumann architecture and to increase miniaturisation.
Gupta, Shini
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Voice activated edge devices using Tiny Machine Learning enabled microcontroller [PDF]
In the ever-evolving landscape of technology, the integration of intelligent and responsive devices into our daily lives has become ubiquitous. From smart homes to industrial settings, the demand for efficient and realtime processing at the edge of ...
Medarametla, Rohit R. +3 more
core +1 more source
Electron, EarlyView.Physics‐driven advances in optical nanobiosensors for rapid, miniaturized, and point‐of‐care diagnostics for next‐generation decentralized and personalized healthcare based on sensor intelligence. ABSTRACT Public health emergencies and the escalating burden of chronic diseases necessitate a paradigm shift from centralized laboratory testing to rapid ...
Vishal Chaudhary +5 more
wiley +1 more source
Classification of gym exercises using tiny machine learning [PDF]
1r Premi TIC Bages 2024Aquesta tesi explora l'aplicació de Tiny Machine Learning (TinyML) per a la classificació d'exercicis del gimnàs utilitzant dispositius de baixa potència a la vora de la xarxa (dispositius Edge).
Graner Babià, Albert
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BioengineeringDiabetes mellitus, a chronic condition affecting millions worldwide, necessitates continuous monitoring of blood glucose level (BGL). The increasing prevalence of diabetes has driven the development of non-invasive methods, such as electronic noses (e ...
Alberto Gudiño-Ochoa +6 more
doaj +1 more source
Learning nondeterministic classifiers [PDF]
, 2009 Nondeterministic classifiers are defined as those allowed to predict more than one class for some entries from an input space. Given that the true class should be included in predictions and the number of classes predicted should be as small as possible,
Coz Velasco, Juan José del +2 more
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