Pareto-based Evaluation of Lightweight AI Models on Embedded Devices

Reproducible framework for evaluating lightweight AI models on low-cost embedded devices using Pareto-based multi-objective analysis. Includes implementations of MLR, MLP and CNN models evaluated on ESP32-S3 and Raspberry Pi platforms.

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Keywords

TinyML, machine learning, Pareto optimization, edge computing, embedded AI

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