Aggregated Residual Transformations for Deep Neural Networks
We present a simple, highly modularized network architecture for image classification. Our network is constructed by repeating a building block that aggregates a set of transformations with the same topology. Our simple design results in a homogeneous, multi-branch architecture that has only a few h...
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Published in | 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 5987 - 5995 |
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Main Authors | , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.07.2017
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Subjects | |
Online Access | Get full text |
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