IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multichannel Approach to Fingerprint Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Classification by Directional Image Partitioning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multicategory Classification by Support Vector Machines
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part I
Artificial Intelligence
A Combination Fingerprint Classifier
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
A Theoretical Study on Six Classifier Fusion Strategies
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiclass LS-SVMs: Moderated Outputs and Coding-Decoding Schemes
Neural Processing Letters
Asymptotic behaviors of support vector machines with Gaussian kernel
Neural Computation
Fast Robust Fingerprint Feature Extraction and Classification
Journal of Intelligent and Robotic Systems
Fingerprint classification: a review
Pattern Analysis & Applications
Probability Estimates for Multi-class Classification by Pairwise Coupling
The Journal of Machine Learning Research
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Support vector machines and the multiple hypothesis test problem
IEEE Transactions on Signal Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Fingerprint classification based on Adaboost learning from singularity features
Pattern Recognition
ConaMSN: A context-aware messenger using dynamic Bayesian networks with wearable sensors
Expert Systems with Applications: An International Journal
Large scale fingerprint mining
Proceedings of the Tenth International Workshop on Multimedia Data Mining
An online core vector machine with adaptive MEB adjustment
Pattern Recognition
Expert Systems with Applications: An International Journal
Multiple classifier method for structured output prediction based on error correcting output codes
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
A fingerprint retrieval system based on level-1 and level-2 features
Expert Systems with Applications: An International Journal
A first study on decomposition strategies with data with class noise using decision trees
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Combining diverse one-class classifiers
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Gait verification using knee acceleration signals
Expert Systems with Applications: An International Journal
Comparison of fuzzy combiner training methods
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
Fingerprint classification by a hierarchical classifier
Pattern Recognition
A survey of multiple classifier systems as hybrid systems
Information Fusion
Artificial Intelligence Review
A framework for selection and fusion of pattern classifiers in multimedia recognition
Pattern Recognition Letters
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Fingerprint classification reduces the number of possible matches in automated fingerprint identification systems by categorizing fingerprints into predefined classes. Support vector machines (SVMs) are widely used in pattern classification and have produced high accuracy when performing fingerprint classification. In order to effectively apply SVMs to multi-class fingerprint classification systems, we propose a novel method in which the SVMs are generated with the one-vs-all (OVA) scheme and dynamically ordered with nai@?ve Bayes classifiers. This is necessary to break the ties that frequently occur when working with multi-class classification systems that use OVA SVMs. More specifically, it uses representative fingerprint features as the FingerCode, singularities and pseudo ridges to train the OVA SVMs and nai@?ve Bayes classifiers. The proposed method has been validated on the NIST-4 database and produced a classification accuracy of 90.8% for five-class classification with the statistical significance. The results show the benefits of integrating different fingerprint features as well as the usefulness of the proposed method in multi-class fingerprint classification.