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TinyML: Progress and applications of machine learning on embedded platforms

openL’apprendimento automatico sta guadagnando sempre più interesse anche nell’ambito dell’elettronica. I motivi principali risiedono nel fatto che le tecniche di Machine Learning richiedono significative quantità di energia e potenza di calcolo per ...
RASERA, NICOLÒ
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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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TinyML Empowered Transfer Learning on the Edge

IEEE Open Journal of the Communications Society
Tiny machine learning (TinyML) is a promising approach to enable intelligent applications relying on Human Activity Recognition (HAR) on resource-limited and low-power Internet of Things (IoT) edge devices.
Ali M. Hayajneh, Maryam Hafeez, Syed Ali Raza Zaidi, Des McLernon   +3 more
doaj   +1 more source

Voice-activated home automation system for IoT edge devices using TinyML

Discover Internet of Things
Home automation systems are popular because they enhance the quality of life and the way users interact with the environment. Deploying complex machine learning models on Internet of Things (IoT) devices with limited resources is still difficult.
Timothy Malche, Sandeep Budhani, Pramod Kumar Soni, Govind Murari Upadhyay   +3 more
doaj   +1 more source

Moving Healthcare AI Support Systems for Visually Detectable Diseases to Constrained Devices

Applied Sciences
Image classification usually requires connectivity and access to the cloud, which is often limited in many parts of the world, including hard-to-reach rural areas.
Tess Watt, Christos Chrysoulas, Peter J. Barclay, Brahim El Boudani, Grigorios Kalliatakis   +4 more
doaj   +1 more source

Learning curves for decision making in supervised machine learning: a survey

Learning curves are a concept from social sciences that has been adopted in the context of machine learning to assess the performance of a learning algorithm with respect to a certain resource, e.g., the number of training examples or the number of ...
van Rijn J.N., Mohr F.
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The need for open source software in machine learning [PDF]

, 2007
Open source tools have recently reached a level of maturity which makes them suitable for building large-scale real-world systems. At the same time, the field of machine learning has developed a large body of powerful learning algorithms for diverse ...
Ratsch, Gunnar, Scholkopf, Bernhard, Vincent, P., LeCun, Y, Ong, C., Braun, M.L., Rasmussen, Carl Edward, Rasmussen, CE, Rätsch, G., Bengio, S., Müller, K.-R., Müller, KR, LeCunn, Yann, Muller, Klaus-Robert, Vincent , P., Pereira, Fernando, Vincent, Pascal, Bottou, Leon, Pereira, F, ,, Braun, ML, Ong, CS, Rasmussen, C.E., Smola, A, Sonnenburg, S., Holmes, G, Bengio, S, Weston, Jason, Williamson, RC, Sonnenburg, S, Williamson, Robert C., Bottou, L., Holmes, G., Ong, Cheng Soon, Pereira, F., Braun, M., Sonnenburg, Soren, Smola, Alexander, Williamson, R.C., Holmes , G., Schölkopf, B, Holmes, Geoffrey, Braun, Mikio L., Bengio, Samy, Schölkopf, B., Rasmussen, C., Williamson, R., Rätch, G, Weston, J, Smola, A., Ong, C.S., Müller, K., Bottou, L, Weston, J., Vincent, P, LeCun, Y.   +55 more
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Integrating Tiny Machine Learning and Edge Computing for Real-Time Object Recognition in Industrial Robotic Arms

Engineering Proceedings
By integrating visual recognition technology and multi-object recognition into robotic arms, the flexibility and automation of the production process were improved in this study.
Nian-Ze Hu, Bo-An Lin, Yen-Yu Wu, Hao-Lun Huang, You-Xin Lin, Chih-Chen Lin, Po-Han Lu   +6 more
doaj   +1 more source

A TinyML Wearable System for Real-Time Cardio-Exercise Tracking

Engineering Proceedings
Cardiovascular exercise strengthens the heart and improves circulation, but most people struggle to fit regular workouts into their day. Short bursts of vigorous activity, sometimes called exercise snacks, can raise the heart rate and deliver meaningful ...
Timothy Malche
doaj   +1 more source

On-device Online-Lernen und semantisches Management von Tiny Machine Learning-Systemen

TinyML (Tiny Machine Learning) aims to democratize ML for microcontrollers. By shifting computation from the cloud to devices, TinyML minimizes communications, enhances privacy, reduces latency, and improves energy efficiency. However, TinyML operates on
Ren, Haoyu
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