A CNN with multi-scale maxout blocks and a circular-filter variance regularizer achieves state-of-the-art accuracy on affine-transformed benchmarks, especially when only 10 training images per class are available.
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Towards Learning Affine-Invariant Representations via Data-Efficient CNNs
A CNN with multi-scale maxout blocks and a circular-filter variance regularizer achieves state-of-the-art accuracy on affine-transformed benchmarks, especially when only 10 training images per class are available.