Feb. 13, 2024, 5:42 a.m. | Justin Davis Mehmet E. Belviranli

cs.LG updates on arXiv.org arxiv.org

In recent years, deep neural networks (DNNs) have gained widespread adoption for continuous mobile object detection (OD) tasks, particularly in autonomous systems. However, a prevalent issue in their deployment is the one-size-fits-all approach, where a single DNN is used, resulting in inefficient utilization of computational resources. This inefficiency is particularly detrimental in energy-constrained systems, as it degrades overall system efficiency. We identify that, the contextual information embedded in the input data stream (e.g. the frames in the camera feed that …

adoption autonomous autonomous systems computational compute context continuous cs.cv cs.lg cs.ro deployment detection dnn issue mobile networks neural networks resources systems tasks

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