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[1905.02244] Searching for MobileNetV3 - arXiv.org
https://arxiv.org/abs/1905.02244
WEBMay 6, 2019 · This paper starts the exploration of how automated search algorithms and network design can work together to harness complementary approaches improving the overall state of the art. Through this process we create two new MobileNet models for release: MobileNetV3-Large and MobileNetV3-Small which are targeted for high and low …
DA: 41 PA: 14 MOZ Rank: 18
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Searching for MobileNetV3 | IEEE Conference Publication | IEEE …
https://ieeexplore.ieee.org/document/9008835
WEBThis paper starts the exploration of how automated search algorithms and network design can work together to harness complementary approaches improving the overall state of the art. Through this process we create two new MobileNet models for release: MobileNetV3-Large and MobileNetV3-Small which are targeted for high and low resource use cases.
DA: 61 PA: 34 MOZ Rank: 25
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[PDF] Searching for MobileNetV3 | Semantic Scholar
https://www.semanticscholar.org/paper/Searching-for-MobileNetV3-Howard-Sandler/5e19eba1e6644f7c83f607383d256deea71f87ae
WEBMay 6, 2019 · This paper starts the exploration of how automated search algorithms and network design can work together to harness complementary approaches improving the overall state of the art. Through this process we create two new MobileNet models for release: MobileNetV3-Large and MobileNetV3-Small which are targeted for high and low …
DA: 84 PA: 89 MOZ Rank: 5
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Searching for MobileNetV3 - arXiv.org
https://arxiv.org/pdf/1905.02244.pdf
WEBexploration of how automated search algorithms and net-work design can work together to harness complementary approaches improving the overall state of the art. Through this process we create two new MobileNet models for re-lease: MobileNetV3-Large and MobileNetV3-Small which are targeted for high and low resource use cases. These
DA: 23 PA: 38 MOZ Rank: 57
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Searching for MobileNetV3 | Papers With Code
https://paperswithcode.com/paper/searching-for-mobilenetv3
WEBMobileNetV3 is tuned to mobile phone CPUs through a combination of hardware-aware network architecture search (NAS) complemented by the NetAdapt algorithm and then …
DA: 46 PA: 50 MOZ Rank: 40
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Searching for MobileNetV3 - arXiv.org
https://arxiv.org/pdf/1905.02244v1.pdf
WEBMobileNetV3 Large and Small models in order to deliver the next generation of high accuracy efficient neural net-work models to power on-device computer vision. The new networks push the state of the art forward and demonstrate how to blend automated search with novel architecture ad-vances to build effective models. 1
DA: 48 PA: 53 MOZ Rank: 36
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Searching for MobileNetV3 - NASA/ADS
https://ui.adsabs.harvard.edu/abs/2019arXiv190502244H/abstract
WEBVasudevan, Vijay. ; Le, Quoc V. ; Adam, Hartwig. We present the next generation of MobileNets based on a combination of complementary search techniques as well as a novel architecture design.
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MobileNet V3 | Papers With Code
https://paperswithcode.com/model/mobilenet-v3
WEBPaper. Code. Config. Weights. README.md. Summary. MobileNetV3 is a convolutional neural network that is designed for mobile phone CPUs. The network design includes the use of a hard swish activation and squeeze-and-excitation modules in the MBConv blocks. How do I load this model? To load a pretrained model:
DA: 95 PA: 36 MOZ Rank: 29
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ICCV 2019 Open Access Repository
https://openaccess.thecvf.com/content_ICCV_2019/html/Howard_Searching_for_MobileNetV3_ICCV_2019_paper.html
WEBSearching for MobileNetV3. Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, Hartwig Adam; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 1314-1324. Abstract.
DA: 90 PA: 8 MOZ Rank: 100
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MobileNetV3 Explained | Papers With Code
https://paperswithcode.com/method/mobilenetv3
WEBIntroduced by Howard et al. in Searching for MobileNetV3. Edit. MobileNetV3 is a convolutional neural network that is tuned to mobile phone CPUs through a combination of hardware-aware network architecture search (NAS) complemented by the NetAdapt algorithm, and then subsequently improved through novel architecture advances.
DA: 95 PA: 7 MOZ Rank: 41
