Deconvolutional networks
暂无分享,去创建一个
[1] Donald Geman,et al. Nonlinear image recovery with half-quadratic regularization , 1995, IEEE Trans. Image Process..
[2] David J. Field,et al. Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.
[3] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[4] Michael A. Saunders,et al. Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..
[5] Yali Amit,et al. A Computational Model for Visual Selection , 1999, Neural Computation.
[6] T. Poggio,et al. Hierarchical models of object recognition in cortex , 1999, Nature Neuroscience.
[7] Refractor. Vision , 2000, The Lancet.
[8] Thomas Serre,et al. Object recognition with features inspired by visual cortex , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[9] Stuart Geman,et al. Context and Hierarchy in a Probabilistic Image Model , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[10] Yoshua Bengio,et al. Greedy Layer-Wise Training of Deep Networks , 2006, NIPS.
[11] 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).
[12] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[13] Marc'Aurelio Ranzato,et al. Efficient Learning of Sparse Representations with an Energy-Based Model , 2006, NIPS.
[14] Zhuowen Tu,et al. Parsing Images into Regions, Curves, and Curve Groups , 2006, International Journal of Computer Vision.
[15] Jitendra Malik,et al. SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[16] Rajat Raina,et al. Efficient sparse coding algorithms , 2006, NIPS.
[17] Sanja Fidler,et al. Towards Scalable Representations of Object Categories: Learning a Hierarchy of Parts , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[18] Song-Chun Zhu,et al. Primal sketch: Integrating structure and texture , 2007, Comput. Vis. Image Underst..
[19] Marc'Aurelio Ranzato,et al. Sparse Feature Learning for Deep Belief Networks , 2007, NIPS.
[20] Rajat Raina,et al. Self-taught learning: transfer learning from unlabeled data , 2007, ICML '07.
[21] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[22] Guillermo Sapiro,et al. Supervised Dictionary Learning , 2008, NIPS.
[23] Sanja Fidler,et al. Similarity-based cross-layered hierarchical representation for object categorization , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[24] Junfeng Yang,et al. A New Alternating Minimization Algorithm for Total Variation Image Reconstruction , 2008, SIAM J. Imaging Sci..
[25] Honglak Lee,et al. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.
[26] Yann LeCun,et al. What is the best multi-stage architecture for object recognition? , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[27] Rob Fergus,et al. Fast Image Deconvolution using Hyper-Laplacian Priors , 2009, NIPS.
[28] Guillermo Sapiro,et al. Online dictionary learning for sparse coding , 2009, ICML '09.
[29] Yihong Gong,et al. Linear spatial pyramid matching using sparse coding for image classification , 2009, CVPR.
[30] Long Zhu,et al. Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[31] Song-Chun Zhu,et al. Primal Sketch: Integrating Texture and Structure , 2011 .