Invariant Scattering Convolution Networks
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[1] P. Abry,et al. Wavelets, spectrum analysis and 1/ f processes , 1995 .
[2] P. Massart,et al. From Model Selection to Adaptive Estimation , 1997 .
[3] Jean-Jacques E. Slotine,et al. On Contraction Analysis for Non-linear Systems , 1998, Autom..
[4] Alexander J. Smola,et al. Learning with kernels , 1998 .
[5] Winfried Stefan Lohmiller,et al. Contraction analysis of nonlinear systems , 1999 .
[6] Michael I. Jordan,et al. On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes , 2001, NIPS.
[7] Yehoshua Y. Zeevi,et al. Gabor Feature Space Diffusion via the Minimal Weighted Area Method , 2001, EMMCVPR.
[8] Bernard Haasdonk,et al. Tangent distance kernels for support vector machines , 2002, Object recognition supported by user interaction for service robots.
[9] Andrew Zisserman,et al. Texture classification: are filter banks necessary? , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[10] Eero P. Simoncelli,et al. A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients , 2000, International Journal of Computer Vision.
[11] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[12] Jitendra Malik,et al. Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons , 2001, International Journal of Computer Vision.
[13] Mario Fritz,et al. On the Significance of Real-World Conditions for Material Classification , 2004, ECCV.
[14] Pietro Perona,et al. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.
[15] Alain Trouvé,et al. Local Geometry of Deformable Templates , 2005, SIAM J. Math. Anal..
[16] Max Welling,et al. Robust Higher Order Statistics , 2005, AISTATS.
[17] Robert E. Broadhurst. Statistical Estimation of Histogram Variation for Texture Classification , 2005 .
[18] Cordelia Schmid,et al. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[19] Yali Amit,et al. POP: Patchwork of Parts Models for Object Recognition , 2007, International Journal of Computer Vision.
[20] Y. Amit,et al. Towards a coherent statistical framework for dense deformable template estimation , 2007 .
[21] Hermann Ney,et al. Deformation Models for Image Recognition , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[22] Marc'Aurelio Ranzato,et al. Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[23] Yoshua Bengio,et al. Exploring Strategies for Training Deep Neural Networks , 2009, J. Mach. Learn. Res..
[24] Yann LeCun,et al. What is the best multi-stage architecture for object recognition? , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[25] Stefano Soatto,et al. Actionable information in vision , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[26] Andrew Zisserman,et al. A Statistical Approach to Material Classification Using Image Patch Exemplars , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Lewis D. Griffin,et al. Using Basic Image Features for Texture Classification , 2010, International Journal of Computer Vision.
[28] Lorenzo Rosasco,et al. On Invariance in Hierarchical Models , 2009, NIPS.
[29] P. Bickel,et al. Covariance regularization by thresholding , 2009, 0901.3079.
[30] Yihong Gong,et al. Locality-constrained Linear Coding for image classification , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[31] Stephane Mollai. Recursive interferometric representations , 2010, EUSIPCO.
[32] Vincent Lepetit,et al. DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[33] Jean Ponce,et al. Learning mid-level features for recognition , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[34] Yann LeCun,et al. Convolutional networks and applications in vision , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.
[35] Zhenhua Guo,et al. Rotation invariant texture classification using LBP variance (LBPV) with global matching , 2010, Pattern Recognit..
[36] Laurent U. Perrinet,et al. Role of Homeostasis in Learning Sparse Representations , 2007, Neural Computation.
[37] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[38] Stéphane Mallat,et al. Group Invariant Scattering , 2011, ArXiv.
[39] Stéphane Mallat,et al. Combined scattering for rotation invariant texture analysis , 2012, ESANN.
[40] Jean Ponce,et al. Task-Driven Dictionary Learning , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[41] J. Lindenstrauss,et al. Fréchet Differentiability of Lipschitz Functions and Porous Sets in Banach Spaces , 2012 .
[42] Alexandre d'Aspremont,et al. Phase recovery, MaxCut and complex semidefinite programming , 2012, Math. Program..