H
Hartwig Adam
Researcher at Google
Publications - 129
Citations - 44746
Hartwig Adam is an academic researcher from Google. The author has contributed to research in topics: Segmentation & Computer science. The author has an hindex of 42, co-authored 116 publications receiving 26381 citations.
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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.
Book ChapterDOI
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
TL;DR: This work extends DeepLabv3 by adding a simple yet effective decoder module to refine the segmentation results especially along object boundaries and applies the depthwise separable convolution to both Atrous Spatial Pyramid Pooling and decoder modules, resulting in a faster and stronger encoder-decoder network.
Posted Content
Rethinking Atrous Convolution for Semantic Image Segmentation
TL;DR: The proposed `DeepLabv3' system significantly improves over the previous DeepLab versions without DenseCRF post-processing and attains comparable performance with other state-of-art models on the PASCAL VOC 2012 semantic image segmentation benchmark.
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.