A Hybrid CRF/HMM for One-Shot Gesture Learning
暂无分享,去创建一个
[1] Suchendra M. Bhandarkar,et al. Integrated detection and tracking of multiple faces using particle filtering and optical flow-based elastic matching , 2009, Comput. Vis. Image Underst..
[2] Flávio Bortolozzi,et al. Segmentation and recognition of handwritten dates: an HMM-MLP hybrid approach , 2003, Document Analysis and Recognition.
[3] Hervé Bourlard,et al. Hybrid Neural Network/Hidden Markov Model Systems for Continuous Speech Recognition , 1993, Int. J. Pattern Recognit. Artif. Intell..
[4] Trevor Darrell,et al. Hidden Conditional Random Fields , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] Gang Qian,et al. A Hybrid HMM/DPA Adaptive Gesture Recognition Method , 2005, ISVC.
[6] C Neidle,et al. SignStream: A tool for linguistic and computer vision research on visual-gestural language data , 2001, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.
[7] Ling Shao,et al. One shot learning gesture recognition from RGBD images , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[8] Isabelle Guyon,et al. ChaLearn gesture challenge: Design and first results , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[9] Dimitris N. Metaxas,et al. A Framework for Recognizing the Simultaneous Aspects of American Sign Language , 2001, Comput. Vis. Image Underst..
[10] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[11] Gerhard Rigoll,et al. Maximum mutual information neural networks for hybrid connectionist-HMM speech recognition systems , 1994, IEEE Trans. Speech Audio Process..
[12] Joseph Picone,et al. Hybrid SVM/HMM architectures for speech recognition , 2000, INTERSPEECH.
[13] Karl-Friedrich Kraiss,et al. Recent developments in visual sign language recognition , 2008, Universal Access in the Information Society.
[14] Emmanuel Augustin,et al. A neural network-hidden Markov model hybrid for cursive word recognition , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).
[15] Gary R. Bradski,et al. Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library , 2016 .
[16] Alex Waibel,et al. Continuous speech recognition using linked predictive neural networks , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.
[17] Alex Acero,et al. Hidden conditional random fields for phone classification , 2005, INTERSPEECH.
[18] Surendra Ranganath,et al. Deciphering gestures with layered meanings and signer adaptation , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..
[19] Ling Shao,et al. One shot learning gesture recognition with Kinect sensor , 2012, ACM Multimedia.
[20] Andrew J. Viterbi,et al. Error bounds for convolutional codes and an asymptotically optimum decoding algorithm , 1967, IEEE Trans. Inf. Theory.
[21] Steve Austin,et al. The forward-backward search algorithm , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.
[22] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[23] Alexander H. Waibel,et al. Continuous Speech Recognition by Linked Predictive Neural Networks , 1990, NIPS.
[24] Jakub Konecný,et al. One-shot-learning gesture recognition using HOG-HOF features , 2014, J. Mach. Learn. Res..
[25] Michel Gilloux,et al. A hybrid radial basis function network/hidden Markov model handwritten word recognition system , 1995, Proceedings of 3rd International Conference on Document Analysis and Recognition.
[26] Andrea Corradini. Real-Time Gesture Recognition by Means of Hybrid Recognizers , 2001, Gesture Workshop.
[27] Marco Gori,et al. A survey of hybrid ANN/HMM models for automatic speech recognition , 2001, Neurocomputing.
[28] L. Baum,et al. Statistical Inference for Probabilistic Functions of Finite State Markov Chains , 1966 .
[29] Harvey F. Silverman,et al. Combining hidden Markov model and neural network classifiers , 1990, International Conference on Acoustics, Speech, and Signal Processing.
[30] Finn Tore Johansen,et al. A comparison of hybrid HMM architecture using global discriminating training , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.
[31] Thierry Artières,et al. Hybrid HMM and HCRF model for sequence classification , 2011, ESANN.
[32] Vladimir I. Levenshtein,et al. Binary codes capable of correcting deletions, insertions, and reversals , 1965 .
[33] Bernadette Dorizzi,et al. Sentence recognition through hybrid neuro-Markovian modeling , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.
[34] Yoshua Bengio,et al. LeRec: A NN/HMM Hybrid for On-Line Handwriting Recognition , 1995, Neural Computation.
[35] Mubarak Shah,et al. Discovering Motion Primitives for Unsupervised Grouping and One-Shot Learning of Human Actions, Gestures, and Expressions , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[36] Yann LeCun,et al. Multi-Digit Recognition Using a Space Displacement Neural Network , 1991, NIPS.
[37] Thierry Paquet,et al. Continuous CRF with Multi-scale Quantization Feature Functions Application to Structure Extraction in Old Newspaper , 2011, 2011 International Conference on Document Analysis and Recognition.
[38] George Zavaliagkos,et al. A Hybrid Continuous Speech Recognition System Using Segmental Neural Nets with Hidden Markov Models , 1993, Int. J. Pattern Recognit. Artif. Intell..
[39] Kenneth M. Sayre,et al. Machine recognition of handwritten words: A project report , 1973, Pattern Recognit..
[40] Simon Thomas,et al. A deep HMM model for multiple keywords spotting in handwritten documents , 2014, Pattern Analysis and Applications.
[41] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.