Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Automatic Recognition of Handwritten Numerical Strings: A Recognition and Verification Strategy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active Handwritten Character Recognition Using Genetic Programming
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Controlled Elitist Non-dominated Sorting Genetic Algorithms for Better Convergence
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Genetical Engineering of Handwriting Representations
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Zoning and metaclasses for character recognition
Proceedings of the 2007 ACM symposium on Applied computing
Thanatos: automatically retrieving information from death certificates in Brazil
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
A multi-objective memetic algorithm for intelligent feature extraction
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Dynamic zoning selection for handwritten character recognition
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Asynchronous master-slave parallelization of differential evolution for multi-objective optimization
Evolutionary Computation
Zoning methods for handwritten character recognition: A survey
Pattern Recognition
| Hi-index | 0.00 |
This paper discusses the use of multi objective evolutionaryalgorithms applied to the engineering of zoning forhandwriten recognition. Usually a task fulfilled by an humanexpert, zoning design relies on specific domain knowledgeand a trial and error process to select an adequatedesign. Our proposed approach to automatically define thezone design was tested and was able to define zoning strategiesthat performed better than our former strategy definedmanually.