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We present the latest generation of MobileNets, known as MobileNetV4 (MNv4), featuring universally efficient architecture designs for mobile devices.
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Han Cai, Chuang Gan, Tianzhe Wang, Zhekai Zhang, and Song Han · 2019
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Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, and Hartwig Adam · 2019
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Noam Shazeer · 2019
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Mingxing Tan and Quoc Le · 2019
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Ekin Dogus Cubuk, Barret Zoph, Jonathon Shlens, and Quoc Le · 2020
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Randaugment: Practical automated data augmentation with a reduced search space
Ekin D Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V Le · 2020
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Ariel N Lee, Cole J Hunter, and Nataniel Ruiz · 2023
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Rethinking vision transformers for mobilenet size and speed
Yanyu Li, Ju Hu, Yang Wen, Georgios Evangelidis, Kamyar Salahi, Yanzhi Wang, Sergey Tulyakov, and Jian Ren · 2023
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Fastvit: A fast hybrid vision transformer using structural reparameterization
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Mobileone: An improved one millisecond mobile backbone
Pavan Kumar Anasosalu Vasu, James Gabriel, Jeff Zhu, Oncel Tuzel, and Anurag Ranjan · 2023
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On the efficiency of convolutional neural networks, 2024
Andrew Lavin · 2024
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