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Andrew Howard
Researcher at Google
Publications - 58
Citations - 46496
Andrew Howard is an academic researcher from Google. The author has contributed to research in topics: Artificial neural network & Object detection. The author has an hindex of 25, co-authored 53 publications receiving 26745 citations. Previous affiliations of Andrew Howard include Columbia University.
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MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew Howard,Menglong Zhu,Bo Chen,Dmitry Kalenichenko,Weijun Wang,Tobias Weyand,M. Andreetto,Hartwig Adam +7 more
TL;DR: This work introduces two simple global hyper-parameters that efficiently trade off between latency and accuracy and demonstrates the effectiveness of MobileNets across a wide range of applications and use cases including object detection, finegrain classification, face attributes and large scale geo-localization.
Proceedings ArticleDOI
MobileNetV2: Inverted Residuals and Linear Bottlenecks
TL;DR: MobileNetV2 as mentioned in this paper is based on an inverted residual structure where the shortcut connections are between the thin bottleneck layers and intermediate expansion layer uses lightweight depthwise convolutions to filter features as a source of non-linearity.
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MobileNetV2: Inverted Residuals and Linear Bottlenecks
TL;DR: A new mobile architecture, MobileNetV2, is described that improves the state of the art performance of mobile models on multiple tasks and benchmarks as well as across a spectrum of different model sizes and allows decoupling of the input/output domains from the expressiveness of the transformation.
Posted Content
Searching for MobileNetV3.
Andrew Howard,Mark Sandler,Grace Chu,Liang-Chieh Chen,Bo Chen,Mingxing Tan,Weijun Wang,Yukun Zhu,Ruoming Pang,Vijay K. Vasudevan,Quoc V. Le,Hartwig Adam +11 more
TL;DR: 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 of MobileNets.
Proceedings ArticleDOI
Searching for MobileNetV3
Andrew Howard,Ruoming Pang,Hartwig Adam,Quoc V. Le,Mark Sandler,Bo Chen,Weijun Wang,Liang-Chieh Chen,Mingxing Tan,Grace Chu,Vijay K. Vasudevan,Yukun Zhu +11 more
TL;DR: MobileNetV3 as mentioned in this paper is the next generation of MobileNets based on a combination of complementary search techniques as well as a novel architecture design and achieves state-of-the-art results for mobile classification, detection and segmentation.