Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
HMM Based On-Line Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representation and Recognition of Handwritten Digits Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Classification on pairwise proximity data
Proceedings of the 1998 conference on Advances in neural information processing systems II
Classification with Nonmetric Distances: Image Retrieval and Class Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Dissimilarity representations allow for building good classifiers
Pattern Recognition Letters
Spatial Representation of Dissimilarity Data via Lower-Complexity Linear and Nonlinear Mappings
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
A Hidden Markov Model-Based Approach to Sequential Data Clustering
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Prototype Selection for Finding Efficient Representations of Dissimilarity Data
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
2D Shape Recognition by Hidden Markov Models
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
A generalized kernel approach to dissimilarity-based classification
The Journal of Machine Learning Research
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Investigating Hidden Markov Models' Capabilities in 2D Shape Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hidden Markov Model Based Continuous Online Gesture Recognition
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Matching pursuits with time-frequency dictionaries
IEEE Transactions on Signal Processing
X-mHMM: An Efficient Algorithm for Training Mixtures of HMMs When the Number of Mixtures Is Unknown
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
An HMM framework for optimal sensor selection with applications to BSN sensor glove design
Proceedings of the 4th workshop on Embedded networked sensors
Dissimilarity between two skeletal trees in a context
Pattern Recognition
2D Shape Classification Using Multifractional Brownian Motion
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Component-based discriminative classification for hidden Markov models
Pattern Recognition
Clustering-Based Construction of Hidden Markov Models for Generative Kernels
EMMCVPR '09 Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Image clustering using local discriminant models and global integration
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Information theoretical Kernels for generative embeddings based on hidden Markov models
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
An empirical evaluation on dimensionality reduction schemes for dissimilarity-based classifications
Pattern Recognition Letters
Hybrid generative-discriminative nucleus classification of renal cell carcinoma
SIMBAD'11 Proceedings of the First international conference on Similarity-based pattern recognition
A multi-classifier system for off-line signature verification based on dissimilarity representation
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Dissimilarity-Based classifications in eigenspaces
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
| Hi-index | 0.01 |
Hidden Markov models (HMM) are a widely used tool for sequence modelling. In the sequence classification case, the standard approach consists of training one HMM for each class and then using a standard Bayesian classification rule. In this paper, we introduce a novel classification scheme for sequences based on HMMs, which is obtained by extending the recently proposed similarity-based classification paradigm to HMM-based classification. In this approach, each object is described by the vector of its similarities with respect to a predetermined set of other objects, where these similarities are supported by HMMs. A central problem is the high dimensionality of resulting space, and, to deal with it, three alternatives are investigated. Synthetic and real experiments show that the similarity-based approach outperforms standard HMM classification schemes.