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Found 2 papers, 1 papers with code
Impact of Thermal Throttling on Long-Term Visual Inference in a CPU-based Edge Device
To assess the performance in outdoor applications, we integrated an external temperature sensor with the RPi4B and conducted a set of experiments with no active cooling in a wide interval of ambient temperature, ranging from 22 {\deg}C to 36 {\deg}C. Variations up to 27. 7% were measured with respect to the maximum throughput achieved in that interval.
PreVIous: A Methodology for Prediction of Visual Inference Performance on IoT Devices
This paper presents PreVIous, a methodology to predict the performance of convolutional neural networks (CNNs) in terms of throughput and energy consumption on vision-enabled devices for the Internet of Things.
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