Method evidence record

MobileNet

MobileNet is a family of lightweight convolutional neural network architectures introduced by Howard et al. at Google in 2017. It is designed to run image classification, object detection, and other vision tasks directly on mobile devices and embedded systems with limited computational budgets. By replacing standard convolutions with depthwise separable convolutions and exposing two global hyperparameters, MobileNet dramatically reduces multiply-add operations and model size while retaining competitive accuracy.

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MobileNet (Efficient Mobile CNN)

Taxonomic method record · ml-model / deep-learning

Howard, A. G., et al. (2017). MobileNets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint. · URL

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Same method familyEfficientNetmachine-suggested · Relational suggestion, not evidence.Same method familyKnowledge Distillationmachine-suggested · Relational suggestion, not evidence.