Dropout Improves Recurrent Neural Networks for Handwriting Recognition
暂无分享,去创建一个
Christopher Kermorvant | Jérôme Louradour | Vu Pham | J. Louradour | Vu Pham | Christopher Kermorvant
[1] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[2] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[3] Anthony J. Robinson,et al. An Off-Line Cursive Handwriting Recognition System , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[4] Sepp Hochreiter,et al. The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions , 1998, Int. J. Uncertain. Fuzziness Knowl. Based Syst..
[5] Sargur N. Srihari,et al. On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[6] Bernadette Dorizzi,et al. Sentence recognition through hybrid neuro-Markovian modeling , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.
[7] Horst Bunke,et al. Using a Statistical Language Model to Improve the Performance of an HMM-Based Cursive Handwriting Recognition System , 2001, Int. J. Pattern Recognit. Artif. Intell..
[8] Horst Bunke,et al. The IAM-database: an English sentence database for offline handwriting recognition , 2002, International Journal on Document Analysis and Recognition.
[9] Michael I. Jordan,et al. Factorial Hidden Markov Models , 1995, Machine Learning.
[10] Jürgen Schmidhuber,et al. Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks , 2006, ICML.
[11] Horst Bunke,et al. Hidden Markov model-based ensemble methods for offline handwritten text line recognition , 2008, Pattern Recognit..
[12] T. Munich,et al. Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks , 2008, NIPS.
[13] J. Schmidhuber,et al. A Novel Connectionist System for Unconstrained Handwriting Recognition , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] Haikal El Abed,et al. ICDAR 2009 Handwriting Recognition Competition , 2009, 2009 10th International Conference on Document Analysis and Recognition.
[15] Hermann Ney,et al. Hierarchical hybrid MLP/HMM or rather MLP features for a discriminatively trained Gaussian HMM: A comparison for offline handwriting recognition , 2011, 2011 18th IEEE International Conference on Image Processing.
[16] Salvador España Boquera,et al. Improving Offline Handwritten Text Recognition with Hybrid HMM/ANN Models , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[17] Christopher Kermorvant,et al. The A2iA French handwriting recognition system at the Rimes-ICDAR2011 competition , 2012, Electronic Imaging.
[18] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[19] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[20] Tara N. Sainath,et al. Improving deep neural networks for LVCSR using rectified linear units and dropout , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[21] Christopher Kermorvant,et al. Handwritten Information Extraction from Historical Census Documents , 2013, 2013 12th International Conference on Document Analysis and Recognition.
[22] Yongqiang Wang,et al. An investigation of deep neural networks for noise robust speech recognition , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[23] Li Deng,et al. A deep convolutional neural network using heterogeneous pooling for trading acoustic invariance with phonetic confusion , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[24] Yann LeCun,et al. Regularization of Neural Networks using DropConnect , 2013, ICML.
[25] Jie Li,et al. Understanding the dropout strategy and analyzing its effectiveness on LVCSR , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[26] Yoshua Bengio,et al. Maxout Networks , 2013, ICML.
[27] Hermann Ney,et al. Improvements in RWTH's System for Off-Line Handwriting Recognition , 2013, 2013 12th International Conference on Document Analysis and Recognition.
[28] Yoshua Bengio,et al. Investigation of recurrent-neural-network architectures and learning methods for spoken language understanding , 2013, INTERSPEECH.
[29] Christopher D. Manning,et al. Fast dropout training , 2013, ICML.
[30] Christopher Kermorvant,et al. The A2iA Arabic Handwritten Text Recognition System at the Open HaRT2013 Evaluation , 2014, 2014 11th IAPR International Workshop on Document Analysis Systems.
[31] Hermann Ney,et al. Multilingual Off-Line Handwriting Recognition in Real-World Images , 2014, 2014 11th IAPR International Workshop on Document Analysis Systems.
[32] Christopher Kermorvant,et al. Over-Generative Finite State Transducer N-Gram for Out-of-Vocabulary Word Recognition , 2014, 2014 11th IAPR International Workshop on Document Analysis Systems.