Name: Nature-Inspired Computation and Machine Learning: 13Th Mexican International Conference on Artificial Intelligence, Micai2014, Tuxtla Gutiérrez,. Part ii (Lecture Notes in Computer Science) (en Inglés)
SKU: 50878162
Price: 1122.11 MXN
Availability: InStock
Author: Alexander Gelbukh
ISBN: 9783319136493

portada Nature-Inspired Computation and Machine Learning: 13Th Mexican International Conference on Artificial Intelligence, Micai2014, Tuxtla Gutiérrez,. Part ii (Lecture Notes in Computer Science) (en Inglés)

Nature-Inspired Computation and Machine Learning: 13Th Mexican International Conference on Artificial Intelligence, Micai2014, Tuxtla Gutiérrez,. Part ii (Lecture Notes in Computer Science) (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Alexander Gelbukh

Año

2014

Idioma

Inglés

N° páginas

522

Encuadernación

Tapa Blanda

ISBN13

9783319136493

N° edición

2014

Categorías

Reconocimiento de formas
Visión por ordenador

Nature-Inspired Computation and Machine Learning: 13Th Mexican International Conference on Artificial Intelligence, Micai2014, Tuxtla Gutiérrez,. Part ii (Lecture Notes in Computer Science) (en Inglés)

Alexander Gelbukh (Autor) · Springer · Tapa Blanda

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Reseña del libro "Nature-Inspired Computation and Machine Learning: 13Th Mexican International Conference on Artificial Intelligence, Micai2014, Tuxtla Gutiérrez,. Part ii (Lecture Notes in Computer Science) (en Inglés)"

The two-volume set LNAI 8856 and LNAI 8857 constitutes the proceedings of the 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. The total of 87 papers plus 1 invited talk presented in these proceedings were carefully reviewed and selected from 348 submissions. The first volume deals with advances in human-inspired computing and its applications. It contains 44 papers structured into seven sections: natural language processing, natural language processing applications, opinion mining, sentiment analysis, and social network applications, computer vision, image processing, logic, reasoning, and multi-agent systems, and intelligent tutoring systems. The second volume deals with advances in nature-inspired computation and machine learning and contains also 44 papers structured into eight sections: genetic and evolutionary algorithms, neural networks, machine learning, machine learning applications to audio and text, data mining, fuzzy logic, robotics, planning, and scheduling, and biomedical applications.