Pareto-based Evaluation of Lightweight AI Models on Embedded Devices

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dc.contributor.authorPatricio Rojas-Carrasco
dc.contributor.authorGuinaldo Losada María
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T21:10:29Z
dc.date.available2026-03-22T21:10:29Z
dc.date.issued2026
dc.description.abstractReproducible 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.
dc.identifier.doi10.5281/zenodo.19002283
dc.identifier.urihttps://doi.org/10.5281/zenodo.19002283
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/86371
dc.publisherEuropean Organization for Nuclear Research
dc.relation.ispartofZenodo (CERN European Organization for Nuclear Research)
dc.sourceUniversidad Central
dc.subjectComputer science
dc.subjectImplementation
dc.subjectEmbedded system
dc.subjectRaspberry pi
dc.subjectArtificial intelligence
dc.titlePareto-based Evaluation of Lightweight AI Models on Embedded Devices
dc.typeother

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