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Adaptation of MobileNetV2 for Face Detection on Ultra-Low Power Platform. (arXiv:2208.11011v1 [cs.CV])
Aug. 24, 2022, 1:11 a.m. | Simon Narduzzi, Engin Türetken, Jean-Philippe Thiran, L. Andrea Dunbar
cs.LG updates on arXiv.org arxiv.org
Designing Deep Neural Networks (DNNs) running on edge hardware remains a
challenge. Standard designs have been adopted by the community to facilitate
the deployment of Neural Network models. However, not much emphasis is put on
adapting the network topology to fit hardware constraints. In this paper, we
adapt one of the most widely used architectures for mobile hardware platforms,
MobileNetV2, and study the impact of changing its topology and applying
post-training quantization. We discuss the impact of the adaptations and …
More from arxiv.org / cs.LG updates on arXiv.org
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