| Título : |
Joint IAPR International Workshop, S+SSPR 2018, Beijing, China, August 17–19, 2018, Proceedings |
| Tipo de documento: |
documento electrónico |
| Autores: |
Bai, Xiao, ; Hancock, Edwin R., ; Ho, Tin Kam, ; Wilson, Richard C., ; Biggio, Battista, ; Robles-Kelly, Antonio, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2018 |
| Número de páginas: |
XIII, 524 p. 134 ilustraciones |
| ISBN/ISSN/DL: |
978-3-319-97785-0 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Palabras clave: |
Sistemas de reconocimiento de patrones Visión por computador Algoritmos Informática Matemáticas discretas Inteligencia artificial Reconocimiento de patrones automatizado Matemáticas discretas en informática Ciencia de los datos |
| Índice Dewey: |
006.3 Inteligencia artificial |
| Resumen: |
Este libro constituye las actas del Taller Internacional Conjunto de la IAPR sobre Reconocimiento de Patrones Estructurales, Sintácticos y Estadísticos, S+SSPR 2018, celebrado en Beijing, China, en agosto de 2018. Los 49 artículos presentados en este volumen fueron cuidadosamente revisados y seleccionados entre 75 presentaciones. Estaban organizados en secciones temáticas denominadas: clasificación y agrupamiento; aprendizaje profundo y redes neuronales; representaciones de disimilitud y procesos gaussianos; métodos de aprendizaje semi y totalmente supervisados; reconocimiento de patrones espacio-temporales y análisis de formas; emparejamiento estructural; análisis y comprensión multimedia; y métodos de teoría de grafos. . |
| Nota de contenido: |
Classification and Clustering -- Image annotation using a semantic hierarchy -- Malignant Brain Tumor Classification using the Random Forest Method -- Rotationally Invariant Bark Recognition -- Dynamic voting in multi-view learning for radiomics applications -- Iterative Deep Subspace Clustering -- A scalable spectral clustering algorithm based on landmark-embedding and cosine similarity -- Deep Learning and Neural Networks -- On Fast Sample Preselection for Speeding up Convolutional Neural Network Training -- UAV First View Landmark Localization via Deep Reinforcement Learning -- Context Free Band Reduction Using a Convolutional Neural Network -- Local Patterns and Supergraph for Chemical Graph Classification with Convolutional Networks -- Learning Deep Embeddings via Margin-based Discriminate Loss -- Dissimilarity Representations and Gaussian Processes -- Protein Remote Homology Detection using Dissimilarity-based Multiple Instance Learning -- Local Binary Patterns based on Subspace Representationof Image Patch for Face Recognition -- An image-based representation for graph classification -- Visual Tracking via Patch-based Absorbing Markov Chain -- Gradient Descent for Gaussian Processes Variance Reduction -- Semi and Fully Supervised Learning Methods -- Sparsification of Indefinite Learning Models -- Semi-supervised Clustering Framework Based on Active Learning for Real Data -- Supervised Classification Using Feature Space Partitioning -- Deep Homography Estimation with Pairwise Invertibility Constraint -- Spatio-temporal Pattern Recognition and Shape Analysis -- Graph Time Series Analysis using Transfer Entropy -- Analyzing Time Series from Chinese Financial Market Using A Linear-Time Graph Kernel -- A Preliminary Survey of Analyzing Dynamic Time-varying Financial Networks Using Graph Kernels -- Few-Example Affine Invariant Ear Detection in the Wild -- Line Voronoi Diagram using Elliptical Distances -- Structural Matching -- Modelling the Generalised Median Correspondence through an Edit Distance -- Learning the Graph Edit Distance edit costs based on an embedded model -- Ring Based Approximation of Graph Edit Distance -- Graph Edit Distance in the exact context -- The VF3-Light Subgraph Isomorphism Algorithm: when doing less is more effective -- A Deep Neural Network Architecture to Estimate Node Assignment Costs for the Graph Edit Distance -- Error-Tolerant Geometric Graph Similarity -- Learning Cost Functions for Graph Matching -- Multimedia Analysis and Understanding -- Matrix Regression-based Classification for Face Recognition -- Plenoptic Imaging for Seeing Through Turbulence -- Weighted Local Mutual Information for 2D-3D Registration in Vascular Interventions -- Cross-model Retrieval with Reconstruct Hashing -- Deep Supervised Hashing with Information Loss -- Single Image Super Resolution via Neighbor Reconstruction -- An Efficient Method for Boundary Detection from Hyperspectral Imagery -- Graph-Theoretic Methods -- Bags of Graphs for Human Action Recognition -- Categorization ofRNA Molecules using Graph Methods -- Quantum Edge Entropy for Alzheimer's Disease Analysis -- Approximating GED using a Stochastic Generator and Multistart IPFP -- Offline Signature Verification by Combining Graph Edit Distance and Triplet Networks -- On Association Graph Techniques for Hypergraph Matching -- Directed Network Analysis using Transfer Entropy Component Analysis -- A Mixed Entropy Local-Global Reproducing Kernel for Attributed Graphs -- Dirichlet Densifiers: Beyond Constraining the Spectral Gap. |
| En línea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
Joint IAPR International Workshop, S+SSPR 2018, Beijing, China, August 17–19, 2018, Proceedings [documento electrónico] / Bai, Xiao, ; Hancock, Edwin R., ; Ho, Tin Kam, ; Wilson, Richard C., ; Biggio, Battista, ; Robles-Kelly, Antonio, . - 1 ed. . - [s.l.] : Springer, 2018 . - XIII, 524 p. 134 ilustraciones. ISBN : 978-3-319-97785-0 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
| Palabras clave: |
Sistemas de reconocimiento de patrones Visión por computador Algoritmos Informática Matemáticas discretas Inteligencia artificial Reconocimiento de patrones automatizado Matemáticas discretas en informática Ciencia de los datos |
| Índice Dewey: |
006.3 Inteligencia artificial |
| Resumen: |
Este libro constituye las actas del Taller Internacional Conjunto de la IAPR sobre Reconocimiento de Patrones Estructurales, Sintácticos y Estadísticos, S+SSPR 2018, celebrado en Beijing, China, en agosto de 2018. Los 49 artículos presentados en este volumen fueron cuidadosamente revisados y seleccionados entre 75 presentaciones. Estaban organizados en secciones temáticas denominadas: clasificación y agrupamiento; aprendizaje profundo y redes neuronales; representaciones de disimilitud y procesos gaussianos; métodos de aprendizaje semi y totalmente supervisados; reconocimiento de patrones espacio-temporales y análisis de formas; emparejamiento estructural; análisis y comprensión multimedia; y métodos de teoría de grafos. . |
| Nota de contenido: |
Classification and Clustering -- Image annotation using a semantic hierarchy -- Malignant Brain Tumor Classification using the Random Forest Method -- Rotationally Invariant Bark Recognition -- Dynamic voting in multi-view learning for radiomics applications -- Iterative Deep Subspace Clustering -- A scalable spectral clustering algorithm based on landmark-embedding and cosine similarity -- Deep Learning and Neural Networks -- On Fast Sample Preselection for Speeding up Convolutional Neural Network Training -- UAV First View Landmark Localization via Deep Reinforcement Learning -- Context Free Band Reduction Using a Convolutional Neural Network -- Local Patterns and Supergraph for Chemical Graph Classification with Convolutional Networks -- Learning Deep Embeddings via Margin-based Discriminate Loss -- Dissimilarity Representations and Gaussian Processes -- Protein Remote Homology Detection using Dissimilarity-based Multiple Instance Learning -- Local Binary Patterns based on Subspace Representationof Image Patch for Face Recognition -- An image-based representation for graph classification -- Visual Tracking via Patch-based Absorbing Markov Chain -- Gradient Descent for Gaussian Processes Variance Reduction -- Semi and Fully Supervised Learning Methods -- Sparsification of Indefinite Learning Models -- Semi-supervised Clustering Framework Based on Active Learning for Real Data -- Supervised Classification Using Feature Space Partitioning -- Deep Homography Estimation with Pairwise Invertibility Constraint -- Spatio-temporal Pattern Recognition and Shape Analysis -- Graph Time Series Analysis using Transfer Entropy -- Analyzing Time Series from Chinese Financial Market Using A Linear-Time Graph Kernel -- A Preliminary Survey of Analyzing Dynamic Time-varying Financial Networks Using Graph Kernels -- Few-Example Affine Invariant Ear Detection in the Wild -- Line Voronoi Diagram using Elliptical Distances -- Structural Matching -- Modelling the Generalised Median Correspondence through an Edit Distance -- Learning the Graph Edit Distance edit costs based on an embedded model -- Ring Based Approximation of Graph Edit Distance -- Graph Edit Distance in the exact context -- The VF3-Light Subgraph Isomorphism Algorithm: when doing less is more effective -- A Deep Neural Network Architecture to Estimate Node Assignment Costs for the Graph Edit Distance -- Error-Tolerant Geometric Graph Similarity -- Learning Cost Functions for Graph Matching -- Multimedia Analysis and Understanding -- Matrix Regression-based Classification for Face Recognition -- Plenoptic Imaging for Seeing Through Turbulence -- Weighted Local Mutual Information for 2D-3D Registration in Vascular Interventions -- Cross-model Retrieval with Reconstruct Hashing -- Deep Supervised Hashing with Information Loss -- Single Image Super Resolution via Neighbor Reconstruction -- An Efficient Method for Boundary Detection from Hyperspectral Imagery -- Graph-Theoretic Methods -- Bags of Graphs for Human Action Recognition -- Categorization ofRNA Molecules using Graph Methods -- Quantum Edge Entropy for Alzheimer's Disease Analysis -- Approximating GED using a Stochastic Generator and Multistart IPFP -- Offline Signature Verification by Combining Graph Edit Distance and Triplet Networks -- On Association Graph Techniques for Hypergraph Matching -- Directed Network Analysis using Transfer Entropy Component Analysis -- A Mixed Entropy Local-Global Reproducing Kernel for Attributed Graphs -- Dirichlet Densifiers: Beyond Constraining the Spectral Gap. |
| En línea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
|  |
Hacer una sugerencia Refinar búsquedaJoint IAPR International Workshop, S+SSPR 2018, Beijing, China, August 17–19, 2018, Proceedings / Bai, Xiao ; Hancock, Edwin R. ; Ho, Tin Kam ; Wilson, Richard C. ; Biggio, Battista ; Robles-Kelly, Antonio
