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Accurate Calibration of Power Measurements from Internal Power Sensors on NVIDIA Jetson Devices
Power efficiency is a crucial consideration for embedded systems design, particularly in the field of edge computing and IoT devices.
Energy Consumption of Neural Networks on NVIDIA Edge Boards: an Empirical Model
At the intersection of these trends, we hence find the energetic characterization of machine learning at the edge, which is attracting increasing attention.
A Simple Framework to Quantify Different Types of Uncertainty in Deep Neural Networks for Image Classification
In this paper we propose a complete framework to capture and quantify three known types of uncertainty in DNNs for the task of image classification.
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