Quantifying Translation-Invariance in Convolutional Neural Networks

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Kauderer-Abrams, Eric;
  • Subject: Computer Science - Computer Vision and Pattern Recognition

A fundamental problem in object recognition is the development of image representations that are invariant to common transformations such as translation, rotation, and small deformations. There are multiple hypotheses regarding the source of translation invariance in CN... View more
  • References (14)
    14 references, page 1 of 2

    [1] Sundaramoorthi, Ganesh, et al. ”On the set of images modulo viewpoint and contrast changes.” Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on. IEEE, 2009.

    [2] LeCun, Yann, et al. ”Gradient-based learning applied to document recognition.” Proceedings of the IEEE 86.11 (1998): 2278-2324.

    [3] Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. ”Imagenet classification with deep convolutional neural networks.” Advances in neural information processing systems. 2012.

    [4] Gens, Robert, and Pedro M. Domingos. ”Deep symmetry networks.” Advances in neural information processing systems. 2014.

    [5] Jaderberg, Max, Karen Simonyan, and Andrew Zisserman. ”Spatial transformer networks.” Advances in Neural Information Processing Systems. 2015.

    [6] LeCun, Yann, Corinna Cortes, and Christopher JC Burges. ”The MNIST database of handwritten digits.” (1998).

    [7] LeCun, Yann. ”Learning invariant feature hierarchies.” Computer vision?ECCV 2012. Workshops and demonstrations. Springer Berlin Heidelberg, 2012.

    [8] Lenc, Karel, and Andrea Vedaldi. ”Understanding image representations by measuring their equivariance and equivalence.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.

    [9] Bruna, Joan, and Stephane Mallat. ”Invariant scattering convolution networks.” Pattern Analysis and Machine Intelligence, IEEE Transactions on 35.8 (2013): 1872- 1886.

    [10] Mallat, Stephane. ”Group invariant scattering.” Communications on Pure and Applied Mathematics 65.10 (2012): 1331-1398.

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