Parsing Natural Scenes and Natural Language with Recursive Neural Networks
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[1] Christoph Goller,et al. Learning task-dependent distributed representations by backpropagation through structure , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).
[2] Yoshua Bengio,et al. A Neural Probabilistic Language Model , 2003, J. Mach. Learn. Res..
[3] Hinrich Schütze,et al. Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.
[4] Dorin Comaniciu,et al. Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[5] James Henderson. Neural Network Probability Estimation for Broad Coverage Parsing , 2003, EACL.
[6] Ben Taskar,et al. Max-Margin Parsing , 2004, EMNLP.
[7] Antonio Torralba,et al. Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.
[8] Alexei A. Efros,et al. Putting Objects in Perspective , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[9] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[10] 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).
[11] Dan Klein,et al. Learning Accurate, Compact, and Interpretable Tree Annotation , 2006, ACL.
[12] Antonio Criminisi,et al. TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation , 2006, ECCV.
[13] Nathan Ratliff,et al. Online) Subgradient Methods for Structured Prediction , 2007 .
[14] Mary P. Harper,et al. Spatial Random Tree Grammars for Modeling Hierarchal Structure in Images with Regions of Arbitrary Shape , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[15] Andrea Vedaldi,et al. Objects in Context , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[16] Jason Weston,et al. A unified architecture for natural language processing: deep neural networks with multitask learning , 2008, ICML '08.
[17] Larry S. Davis,et al. Beyond Nouns: Exploiting Prepositions and Comparative Adjectives for Learning Visual Classifiers , 2008, ECCV.
[18] Honglak Lee,et al. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.
[19] Stephen Gould,et al. Decomposing a scene into geometric and semantically consistent regions , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[20] Li Fei-Fei,et al. Towards total scene understanding: Classification, annotation and segmentation in an automatic framework , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[21] Fei-Fei Li,et al. Connecting modalities: Semi-supervised segmentation and annotation of images using unaligned text corpora , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[22] Christopher D. Manning,et al. Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks , 2010 .
[23] Svetlana Lazebnik,et al. Superparsing , 2010, International Journal of Computer Vision.
[24] Antonio Torralba,et al. Part and appearance sharing: Recursive Compositional Models for multi-view , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.