Survey and bibliography of Arabic optical text recognition
Signal Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Experimental evaluation of expert fusion strategies
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
An approach to the automatic design of multiple classifier systems
Pattern Recognition Letters - Special issue on machine learning and data mining in pattern recognition
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
HMM Based Approach for Handwritten Arabic Word Recognition Using the IFN/ENIT- Database
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Printed PAW Recognition Based on Planar Hidden Markov Models
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Using diversity of errors for selecting members of a committee classifier
Pattern Recognition
Pairwise fusion matrix for combining classifiers
Pattern Recognition
Using weighted dynamic classifier selection methods in ensembles with different levels of diversity
International Journal of Hybrid Intelligent Systems - Hybrid Intelligent systems in Ensembles
Pattern Recognition Letters
Incremental construction of classifier and discriminant ensembles
Information Sciences: an International Journal
Editorial: New Frontiers in Handwriting Recognition
Pattern Recognition
Classifiers combination and syntax analysis for Arabic literal amount recognition
Engineering Applications of Artificial Intelligence
Comparison of classifier selection methods for improving committee performance
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Arabic handwriting recognition using structural and syntactic pattern attributes
Pattern Recognition
New dynamic classifiers selection approach for handwritten recognition
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Offline arabic handwritten text recognition: A Survey
ACM Computing Surveys (CSUR)
International Journal of Knowledge-based and Intelligent Engineering Systems
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The first observation concerning Arabian manuscript reveals the complexity of the task, especially for the used classifiers ensemble. One of the most important steps in the design of a multi-classifier system (MCS), is the its components choice (classifiers). This step is very important to the overall MCS performance since the combination of a set of identical classifiers will not outperform the individual members. To select the best classifier set from a pool of classifiers, the classifier diversity is the most important property to be considered. The aim of this paper is to study Arabic handwriting recognition using MCS optimization based on diversity measures. The first approach selects the best classifier subset from large classifiers set taking into account different diversity measures. The second one chooses among the classifier set the one with the best performance and adds it to the selected classifiers subset. The performance in our approach is calculated using three diversity measures based on correlation between errors. On two database sets using 9 different classifiers, we then test the effect of using the criterion to be optimized (diversity measures,), and fusion methods (voting, weighted voting and Behavior Knowledge Space). The experimental results presented are encouraging and open other perspectives in the classifiers selection field especially speaking for Arabic Handwritten word recognition.