Recommending Pre-Trained Models for IoT Devices

The availability of pre-trained models (PTMs) has enabled faster deployment of machine learning across applications by reducing the need for extensive training. Techniques like quantization and distillation have further expanded PTM applicability to resource-constrained IoT hardware. Given the many...

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Vydané v:	IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Technologies Results (Online) s. 126 - 130
Hlavní autori:	Patil, Parth V., Jiang, Wenxin, Peng, Huiyun, Lugo, Daniel, Kalu, Kelechi G., LeBlanc, Josh, Smith, Lawrence, Heo, Hyeonwoo, Aou, Nathanael, Davis, James C.
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 27.04.2025
Predmet:	Hardware Internet of Things IoT Machine learning Model Recommendation Object recognition Pre-Trained Models Quantization (signal) Recommender systems Software engineering Training Tuning
ISSN:	2832-7632
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