This book constitutes the refereed proceedings of the 6th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2018, held in Havana, Cuba, in September 2018. The 42 full papers presented were carefully reviewed and selected from 101 submissions. The papers promote and disseminate ongoing research on mathematical methods and computing techniques for artificial intelligence and pattern recognition, in particular in bioinformatics, cognitive and humanoid vision, computer vision, image analysis and intelligent data analysis, as well as their application in a number of diverse areas such as industry, health, robotics, data mining, opinion mining and sentiment analysis, telecommunications, document analysis, and natural language processing and recognition.

The two-volume set LNCS 8258 and 8259 constitutes the refereed proceedings of the 18th Iberoamerican Congress on Pattern Recognition, CIARP 2013, held in Havana, Cuba, in November 2013. The 137 papers presented, together with two keynotes, were carefully reviewed and selected from 262 submissions. The papers are organized in topical sections on mathematical theory of PR, supervised and unsupervised classification, feature or instance selection for classification, image analysis and retrieval, signals analysis and processing, applications of pattern recognition, biometrics, video analysis, and data mining.

The two-volume set LNCS 8258 and 8259 constitutes the refereed proceedings of the 18th Iberoamerican Congress on Pattern Recognition, CIARP 2013, held in Havana, Cuba, in November 2013. The 137 papers presented, together with two keynotes, were carefully reviewed and selected from 262 submissions. The papers are organized in topical sections on mathematical theory of PR, supervised and unsupervised classification, feature or instance selection for classification, image analysis and retrieval, signals analysis and processing, applications of pattern recognition, biometrics, video analysis, and data mining.

This book constitutes the refereed proceedings of the 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, held in Havana, Cuba, in September 2008.

The 93 revised full papers presented together with 3 keynote articles were carefully reviewed and selected from 182 submissions. The papers are organized in topical sections on signal analysis for characterization and filtering, analysis of shape and texture, analysis of speech and language, data mining, clustering of images and documents, statistical pattern recognition, classification and description of objects, classification and edition, geometric image analysis, neural networks, computer vision, image coding, associative memories and neural networks, interpolation and video tracking, images analysis, music and speech analysis, as well as classifier combination and document filtering.

CIARP 2003 (8th Iberoamerican Congress on Pattern Recognition) was the eighth event in a series of pioneering congresses on pattern recognition in the Latin American c- munity of countries. This year, however, the forum was extended to include worldwide participation. The event has been held in the past in Mexico, Cuba, Brazil and Por- gal; it took place this year in Havana (Cuba). The aim of the congress was to promote and disseminate ongoing research into mathematical methods for pattern recognition, computer vision, image analysis, and speech recognition, as well as the application of these techniques in such diverse areas as robotics, industry, health, entertainment, space exploration, telecommunications, data mining, document analysis, and natural language processing and recognition to name a few. Moreover it was a forum for scienti?c re- arch, experience exchange, the sharing of new knowledge, and establishing contacts to improve cooperation between research groups in pattern recognition, computer vision and related areas. The congress was organized by the Institute of Cybernetics, Mathematics and P- sics of Cuba (ICIMAF) and the Center for Computing Research (CIC) of the National Polytechnic Institute of Mexico, and was sponsored by the University of La Salle, - xico, the University of Oriente, Cuba, the Polytechnic Institute Jose A."

This book constitutes the refereed proceedings of the 7th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2021, held in Havana, Cuba, in October 2021. The 42 full papers presented were carefully reviewed and selected from 73 submissions. The papers promote and disseminate ongoing research on mathematical methods and computing techniques for artificial intelligence and pattern recognition, in particular in bioinformatics, cognitive and humanoid vision, computer vision, image analysis and intelligent data analysis.

ALVOT (ALgoritmos de VOTacion) es un modelo de algoritmos de clasificacion supervisada basado en precedencias parciales que permite trabajar con descripciones de objetos en terminos de variables numericas y no numericas simultaneamente e incluso admite valores desconocidos en las mismas. Este ha sido utilizado en numerosos problemas practicos en las denominadas ciencias poco formalizadas ("soft sciences") como por ejemplo las geociencias, la medicina, la criminalistica y otras. Los clasificadores ALVOT, como todos los clasificadores supervisados en general, necesitan de una "buena" matriz de entrenamiento para lograr clasificar con calidad; de aqui que sea un problema determinar que objetos se deben seleccionar para el entrenamiento de los mismos. Es por esto que en el presente trabajo se proponen dos metodos de seleccion de objetos; el primero para mejorar la eficiencia sin afectar la eficacia sustancialmente de los clasificadores ALVOT, y el segundo para mejorar la eficacia al trabajar con bases de datos ruidosas.