Pareto Optimal Benchmarking of AI Models on ARM Cortex Processors for Sustainable Embedded Systems | ScienceToStartup | ScienceToStartup

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References (14)

[1]

Analysing Edge Computing Devices for the Deployment of Embedded AI

2023Asier Garcia-Perez, Raúl Miñón et al.

[2]

Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML

2023Mark Deutel, G. Kontes et al.

[3]

DeepEdgeBench: Benchmarking Deep Neural Networks on Edge Devices

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"Benchmarking framework for optimizing AI models on ARM Cortex processors to ensure energy-efficient embedded systems."

Embedded AI•Score: 5•View PDF ↗

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Pareto Optimal Benchmarking of AI Models on ARM Cortex Processors for Sustainable Embedded Systems

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"Benchmarking framework for optimizing AI models on ARM Cortex processors to ensure energy-efficient embedded systems."

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Pareto Optimal Benchmarking of AI Models on ARM Cortex Processors for Sustainable Embedded Systems

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"Benchmarking framework for optimizing AI models on ARM Cortex processors to ensure energy-efficient embedded systems."

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