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Follmann et al., 2018 - Google Patents

A rotationally-invariant convolution module by feature map back-rotation

Follmann et al., 2018

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Document ID
3163667089729684006
Author
Follmann P
Bottger T
Publication year
Publication venue
2018 IEEE Winter Conference on Applications of Computer Vision (WACV)

External Links

Snippet

Despite breakthroughs in image classification due to the evolution of deep learning and, in particular, convolutional neural networks (CNNs), state-of-the-art models only possess a very limited amount of rotational invariance. Known workarounds include artificial rotations …
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