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CONTROLLING PERFORMANCE OF DEPLOYED DEEP LEARNING MODELS ON RESOURCE CONSTRAINED EDGE DEVICE VIA PREDICTIVE MODELS
CONTROLLING PERFORMANCE OF DEPLOYED DEEP LEARNING MODELS ON RESOURCE CONSTRAINED EDGE DEVICE VIA PREDICTIVE MODELS
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机译:通过预测模型控制资源约束边缘设备上部署深度学习模型的性能
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摘要
An example system includes a processor to receive a data input and a predicted performance of a Deep Learning (DL) model deployed on a resource constrained edge device from a predictive model. The processor is to modify a control input for the DL model based on the data input and the predicted performance. The processor is to send the control input to the deployed DL model to modify performance of the DL model.
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