| TÃtulo : |
Pattern Recognition : 10th Mexican Conference, MCPR 2018, Puebla, Mexico, June 27-30, 2018, Proceedings |
| Tipo de documento: |
documento electrónico |
| Autores: |
MartÃnez-Trinidad, José Francisco, ; Carrasco-Ochoa, Jesús Ariel, ; Olvera-López, José Arturo, ; Sarkar, Sudeep, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2018 |
| Número de páginas: |
XI, 288 p. 113 ilustraciones |
| ISBN/ISSN/DL: |
978-3-319-92198-3 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Idioma : |
Inglés (eng) |
| Palabras clave: |
Sistemas de reconocimiento de patrones Inteligencia artificial Visión por computador Reconocimiento de patrones automatizado |
| Clasificación: |
006.4 |
| Resumen: |
Este libro constituye las actas de la Décima Conferencia Mexicana sobre Reconocimiento de Patrones, MCPR 2018, celebrada en Puebla, México, en junio de 2018. Los 28 artÃculos presentados en este volumen fueron cuidadosamente revisados ​​y seleccionados entre 44 presentaciones. Estaban organizados en secciones temáticas denominadas: principios de reconocimiento de patrones; aprendizaje profundo, redes neuronales y memorias asociativas; procesamiento de datos; y visión por computadora. . |
| Nota de contenido: |
Pattern Recognition Principles -- Patterns of Go gaming by Ising model -- A Novel Criterion to Obtain the Best Feature Subset from Filter Ranking Methods -- Class-specific Reducts vs. Classic Reducts in a Rule-based Classifier: A Case Study -- On the Construction of a Specific Algebra for Composing Tonal Counterpoint -- The Impact of Basic Matrix Dimension on the Performance of Algorithms for Computing Typical Testors -- Fast Convex Hull by a Geometric Approach -- An Experimental Study on Ant Colony Optimization Hyper-heuristics for Solving the Knapsack Problem -- A Linear Time Algorithm for Computing #2SAT for Outerplanar 2-CNF Formulas -- Improving the List of Clustered Permutation on Metric Spaces for Similarity Searching on Secondary Memory -- Modelling 3-Coloring of Polygonal Trees via Incremental Satisfiability -- Deep Learning, Neural Networks and Associative Memories -- Performance Analysis of Deep Neural Networks for Classification of Gene-Expression Microarrays -- Extreme Points of Convex Polytopes Derived from Lattice Autoassociative Memories -- A Comparison of Deep Neural Network Algorithms for Recognition of EEG Motor Imagery Signals -- Learning Word and Sentence Embeddings using a Generative Convolutional Network -- Dense Captioning of Natural Scenes in Spanish -- Automated Detection of Hummingbirds in Images: a Deep Learning Approach -- Data Mining -- Patterns in Poor Learning Engagement in Students While They are Solving Mathematics Exercises in an Affective Tutoring System Related to Frustration -- Pattern Discovery in Mixed Data Bases -- Image Clustering based on Frequent Approximate Subgraph Mining -- Validation of Semantic Relation of Synonymy in Domain Ontologies using Lexico-Syntactic Patterns and Acronyms -- Computer Vision -- Scene Text Segmentation Based on Local Image Phase Information and MSER Method -- A Lightweight Library for Augmented Reality Applications -- Point Set Matching with Order Type -- Including Foreground and Background Information in Maya Hieroglyph Representation -- A Fast Algorithm for Robot Localization using Multiple Sensing Units -- Improving Breast Mass Classification through Kernel Methods and the Fusion of Clinical Data and Image Descriptors -- An Improved Stroke Width Transform to Detect Race Bib Numbers -- Scaled CCR Histogram for Scale-invariant Texture Classification. |
| Tipo de medio : |
Computadora |
| Summary : |
This book constitutes the proceedings of the 10th Mexican Conference on Pattern Recognition, MCPR 2018, held in Puebla, Mexico, in June 2018. The 28 papers presented in this volume were carefully reviewed and selected from 44 submissions. They were organized in topical sections named: pattern recognition principles; deep learning, neural networks and associative memories; data mining; and computer vision. . |
| Enlace de acceso : |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
Pattern Recognition : 10th Mexican Conference, MCPR 2018, Puebla, Mexico, June 27-30, 2018, Proceedings [documento electrónico] / MartÃnez-Trinidad, José Francisco, ; Carrasco-Ochoa, Jesús Ariel, ; Olvera-López, José Arturo, ; Sarkar, Sudeep, . - 1 ed. . - [s.l.] : Springer, 2018 . - XI, 288 p. 113 ilustraciones. ISBN : 978-3-319-92198-3 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés ( eng)
| Palabras clave: |
Sistemas de reconocimiento de patrones Inteligencia artificial Visión por computador Reconocimiento de patrones automatizado |
| Clasificación: |
006.4 |
| Resumen: |
Este libro constituye las actas de la Décima Conferencia Mexicana sobre Reconocimiento de Patrones, MCPR 2018, celebrada en Puebla, México, en junio de 2018. Los 28 artÃculos presentados en este volumen fueron cuidadosamente revisados ​​y seleccionados entre 44 presentaciones. Estaban organizados en secciones temáticas denominadas: principios de reconocimiento de patrones; aprendizaje profundo, redes neuronales y memorias asociativas; procesamiento de datos; y visión por computadora. . |
| Nota de contenido: |
Pattern Recognition Principles -- Patterns of Go gaming by Ising model -- A Novel Criterion to Obtain the Best Feature Subset from Filter Ranking Methods -- Class-specific Reducts vs. Classic Reducts in a Rule-based Classifier: A Case Study -- On the Construction of a Specific Algebra for Composing Tonal Counterpoint -- The Impact of Basic Matrix Dimension on the Performance of Algorithms for Computing Typical Testors -- Fast Convex Hull by a Geometric Approach -- An Experimental Study on Ant Colony Optimization Hyper-heuristics for Solving the Knapsack Problem -- A Linear Time Algorithm for Computing #2SAT for Outerplanar 2-CNF Formulas -- Improving the List of Clustered Permutation on Metric Spaces for Similarity Searching on Secondary Memory -- Modelling 3-Coloring of Polygonal Trees via Incremental Satisfiability -- Deep Learning, Neural Networks and Associative Memories -- Performance Analysis of Deep Neural Networks for Classification of Gene-Expression Microarrays -- Extreme Points of Convex Polytopes Derived from Lattice Autoassociative Memories -- A Comparison of Deep Neural Network Algorithms for Recognition of EEG Motor Imagery Signals -- Learning Word and Sentence Embeddings using a Generative Convolutional Network -- Dense Captioning of Natural Scenes in Spanish -- Automated Detection of Hummingbirds in Images: a Deep Learning Approach -- Data Mining -- Patterns in Poor Learning Engagement in Students While They are Solving Mathematics Exercises in an Affective Tutoring System Related to Frustration -- Pattern Discovery in Mixed Data Bases -- Image Clustering based on Frequent Approximate Subgraph Mining -- Validation of Semantic Relation of Synonymy in Domain Ontologies using Lexico-Syntactic Patterns and Acronyms -- Computer Vision -- Scene Text Segmentation Based on Local Image Phase Information and MSER Method -- A Lightweight Library for Augmented Reality Applications -- Point Set Matching with Order Type -- Including Foreground and Background Information in Maya Hieroglyph Representation -- A Fast Algorithm for Robot Localization using Multiple Sensing Units -- Improving Breast Mass Classification through Kernel Methods and the Fusion of Clinical Data and Image Descriptors -- An Improved Stroke Width Transform to Detect Race Bib Numbers -- Scaled CCR Histogram for Scale-invariant Texture Classification. |
| Tipo de medio : |
Computadora |
| Summary : |
This book constitutes the proceedings of the 10th Mexican Conference on Pattern Recognition, MCPR 2018, held in Puebla, Mexico, in June 2018. The 28 papers presented in this volume were carefully reviewed and selected from 44 submissions. They were organized in topical sections named: pattern recognition principles; deep learning, neural networks and associative memories; data mining; and computer vision. . |
| Enlace de acceso : |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
|  |
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