A note on genetic algorithms for large-scale feature selection
Pattern Recognition Letters
Recognizing Handwritten Digits Using Hierarchical Products of Experts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theoretical Study on Six Classifier Fusion Strategies
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing: PIKS Inside
Digital Image Processing: PIKS Inside
On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
Data Mining and Knowledge Discovery
Training Invariant Support Vector Machines
Machine Learning
Theoretical and Experimental Analysis of a Two-Stage System for Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel feature extraction method and hybrid tree classification for handwritten numeral recognition
Pattern Recognition Letters
Handwritten Digit Recognition Using State-of-the-Art Techniques
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Rejection Strategies for Offline Handwritten Sentence Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Extraction of Hybrid Complex Wavelet Features for the Verification of Handwritten Numerals
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Analysis of errors of handwritten digits made by a multitude of classifiers
Pattern Recognition Letters - Special issue: In memoriam Azriel Rosenfeld
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
An Interactive System for Reading Unformatted Printed Text
IEEE Transactions on Computers
Neural Computation
Dimensionality reduction using genetic algorithms
IEEE Transactions on Evolutionary Computation
On optimum recognition error and reject tradeoff
IEEE Transactions on Information Theory
A multiexpert framework for character recognition: a novel application of Clifford networks
IEEE Transactions on Neural Networks
Robust Handwritten Character Recognition with Features Inspired by Visual Ventral Stream
Neural Processing Letters
An Approach to Searching for Two-Dimensional Cellular Automata for Recognition of Handwritten Digits
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Journal of Real-Time Image Processing
Binary segmentation algorithm for English cursive handwriting recognition
Pattern Recognition
On-line multi-stage sorting algorithm for agriculture products
Pattern Recognition
Off-line cursive script recognition: current advances, comparisons and remaining problems
Artificial Intelligence Review
A cascade face recognition system using hybrid feature extraction
Digital Signal Processing
An efficient way of combining SVMs for handwritten digit recognition
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Feature representation selection based on Classifier Projection Space and Oracle analysis
Expert Systems with Applications: An International Journal
Serial fusion of random subspace ensemble for subcellular phenotype images classification
International Journal of Bioinformatics Research and Applications
ACM Transactions on Embedded Computing Systems (TECS)
A novel free format Persian/Arabic handwritten zip code recognition system
Computers and Electrical Engineering
Breast cancer diagnosis from biopsy images with highly reliable random subspace classifier ensembles
Machine Vision and Applications
Hybrid model of clustering and kernel autoassociator for reliable vehicle type classification
Machine Vision and Applications
Random subspace support vector machine ensemble for reliable face recognition
International Journal of Biometrics
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This paper presents a novel cascade ensemble classifier system for the recognition of handwritten digits. This new system aims at attaining a very high recognition rate and a very high reliability at the same time, in other words, achieving an excellent recognition performance of handwritten digits. The trade-offs among recognition, error, and rejection rates of the new recognition system are analyzed. Three solutions are proposed: (i) extracting more discriminative features to attain a high recognition rate, (ii) using ensemble classifiers to suppress the error rate and (iii) employing a novel cascade system to enhance the recognition rate and to reduce the rejection rate. Based on these strategies, seven sets of discriminative features and three sets of random hybrid features are extracted and used in the different layers of the cascade recognition system. The novel gating networks (GNs) are used to congregate the confidence values of three parallel artificial neural networks (ANNs) classifiers. The weights of the GNs are trained by the genetic algorithms (GAs) to achieve the overall optimal performance. Experiments conducted on the MNIST handwritten numeral database are shown with encouraging results: a high reliability of 99.96% with minimal rejection, or a 99.59% correct recognition rate without rejection in the last cascade layer.