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Autor Tino, Peter |
Documentos disponibles escritos por este autor (3)
Crear una solicitud de compra Refinar búsquedaIntelligent Data Engineering and Automated Learning – IDEAL 2019 / Yin, Hujun ; Camacho, David ; Tino, Peter ; Tallón-Ballesteros, Antonio J. ; Menezes, Ronaldo ; Allmendinger, Richard
TÃtulo : Intelligent Data Engineering and Automated Learning – IDEAL 2019 : 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I / Tipo de documento: documento electrónico Autores: Yin, Hujun, ; Camacho, David, ; Tino, Peter, ; Tallón-Ballesteros, Antonio J., ; Menezes, Ronaldo, ; Allmendinger, Richard, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2019 Número de páginas: XXII, 554 p. 213 ilustraciones, 141 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-33607-3 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: Inteligencia artificial IngenierÃa Informática y Redes Aplicaciones informáticas y de sistemas de información TeorÃa de la Computación Computadoras y Educación MinerÃa de datos y descubrimiento de conocimientos IngenierÃa Informática Application software Informática Procesamiento de datos Red informática Educación Clasificación: 6.312 Resumen: Este conjunto de dos volúmenes de LNCS 11871 y 11872 constituye las actas de la 20.ª Conferencia Internacional sobre IngenierÃa de Datos Inteligentes y Aprendizaje Automatizado, IDEAL 2019, celebrada en Manchester, Reino Unido, en noviembre de 2019. Los 94 artÃculos completos presentados fueron cuidadosamente revisados. y seleccionado entre 149 presentaciones. Estos artÃculos proporcionaron una muestra oportuna de los últimos avances en ingenierÃa de datos y aprendizaje automático, desde metodologÃas, marcos y algoritmos hasta aplicaciones. Los temas centrales de IDEAL 2019 incluyen desafÃos de big data, aprendizaje automático, minerÃa de datos, recuperación y gestión de información, bioinformática/neuroinformática, modelos bioinspirados (incluidas redes neuronales, computación evolutiva e inteligencia de enjambre), agentes y sistemas inteligentes hÃbridos. , aplicaciones del mundo real de técnicas inteligentes e IA. Nota de contenido: Orchids Classification Using Spatial Transformer Network with Adaptive Scaling -- Scalable Dictionary Classifiers for Time Series Classification -- Optimization of the numeric and categorical attribute weights in KAMILA mixed data clustering algorithm -- Meaningful Data Sampling for a Faithful Local Explanation Method -- Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor -- Adaptive Orthogonal Characteristics of Bio-inspired Neural Networks -- Using Deep Learning for Ordinal Classification of Mobile Marketing User Conversion -- Modeling Data Driven Interactions on Property Graph -- Adaptive Dimensionality Adjustment for Online "Principal Component Analysis" -- Relevance Metric for Counterfactuals Selection in Decision Trees -- Weighted Nearest Centroid Neighbourhood -- The Prevalence of Errors in Machine Learning Experiments -- A Hybrid Model for Fraud Detection on Purchase Orders -- Users Intention based on Twitter Features using Text Analytics -- Mixing hetero- and homogeneous models in weighted ensembles -- A Hybrid Approach to Time Series Classification with Shapelets -- An Ensemble Algorithm Based on Deep Learning for Tuberculosis Classification -- A Data-driven Approach to Automatic Extraction of Professional Figure Profiles from Résumés -- Retrieving and Processing Information from Clinical Algorithm via Formal Concept Analysis -- Comparative Analysis of Approaches to Building Medical Dialog Systems in Russian -- Tracking Position and Status of Electric Control Switches Based on YOLO Detector -- A Self-Generating Prototype method based on Information Entropy used for Condensing Data in Classification Tasks -- Transfer Knowledge between Sub-regions for Traffic Prediction using Deep Learning Method -- Global Q-Learning Approach for Power Allocation in Femtocell Networks -- Deep learning and Sensor Fusion Methods for Studying Gait Changes under Cognitive Load in Males and Females -- Towards a robotic personaltrainer for the elderly -- Image Quality Constrained GAN for Super-Resolution -- Use Case Prediction using Product Reviews Text Classification -- Convolutional Neural Network for Core Sections Identification in Scientific Research Publications -- Knowledge Inference Through Analysis of Human Activities -- Representation Learning of Knowledge Graphs with Multi-scale Capsule Network -- CNNPSP: Pseudouridine Sites Prediction Based on Deep Learning -- A Multimodal Approach to Image Sentiment Analysis -- Joining Items Clustering and Users Clustering for Evidential Collaborative Filtering -- Conditioned Generative Model via Latent Semantic Controlling for Learning Deep Representation of Data -- Toward A Framework for Seasonal Time Series Forecasting Using Clustering -- An Evidential Imprecise Answer Aggregation Approach based on Worker Clustering -- Combining Machine Learning and Classical Optimization Techniques in Vehicle to Vehicle Communication Network -- Adversarial Edit Attacks for Tree Data -- Non-stationary Noise Cancellation Using Deep Autoencoder based on Adversarial Learning -- A Deep Learning-based Surface Defect Inspection System for Smartphone Glass -- Superlinear Speedup of Parallel Population-based Metaheuristics: A Microservices and Container Virtualization Approach -- Active Dataset Generation for Meta-Learning System Quality Improvement -- Do You Really Follow Them? Automatic Detection of Credulous Twitter Users -- User Localization Based on Call Detail Record -- Automatic Ground Truth Dataset Creation for Fake News Detection in Social Media -- Artificial Flora Optimization Algorithm for Task Scheduling in Cloud Computing Environment -- A Significantly Faster Elastic-Ensemble for Time-Series Classification -- ALIME: Autoencoder Based Approach for Local Interpretability -- Detection of Abnormal Load Consumption in the Power Grid Using Clustering and Statistical Analysis -- Deep Convolutional Neural Networks Based on Image Data Augmentation for Visual Object Recognition -- An Efficient Scheme for Prototyping kNN in the Context of Real-Time Human Activity Recognition -- A Novel Recommendation System for Next Feature in Software -- Meta-learning Based Evolutionary Clustering Algorithm -- Fast tree-based classification via homogeneous clustering -- Ordinal equivalence classes for parallel coordinates -- New Internal Clustering Evaluation Index Based on Line Segments -- Threat Identification in Humanitarian Demining using Machine Learning and Spectroscopic Metal Detection. Tipo de medio : Computadora Summary : This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019. The 94 full papers presented were carefully reviewed and selected from 149 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2019 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models (including neural networks, evolutionary computation and swarm intelligence), agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Intelligent Data Engineering and Automated Learning – IDEAL 2019 : 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I / [documento electrónico] / Yin, Hujun, ; Camacho, David, ; Tino, Peter, ; Tallón-Ballesteros, Antonio J., ; Menezes, Ronaldo, ; Allmendinger, Richard, . - 1 ed. . - [s.l.] : Springer, 2019 . - XXII, 554 p. 213 ilustraciones, 141 ilustraciones en color.
ISBN : 978-3-030-33607-3
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: Inteligencia artificial IngenierÃa Informática y Redes Aplicaciones informáticas y de sistemas de información TeorÃa de la Computación Computadoras y Educación MinerÃa de datos y descubrimiento de conocimientos IngenierÃa Informática Application software Informática Procesamiento de datos Red informática Educación Clasificación: 6.312 Resumen: Este conjunto de dos volúmenes de LNCS 11871 y 11872 constituye las actas de la 20.ª Conferencia Internacional sobre IngenierÃa de Datos Inteligentes y Aprendizaje Automatizado, IDEAL 2019, celebrada en Manchester, Reino Unido, en noviembre de 2019. Los 94 artÃculos completos presentados fueron cuidadosamente revisados. y seleccionado entre 149 presentaciones. Estos artÃculos proporcionaron una muestra oportuna de los últimos avances en ingenierÃa de datos y aprendizaje automático, desde metodologÃas, marcos y algoritmos hasta aplicaciones. Los temas centrales de IDEAL 2019 incluyen desafÃos de big data, aprendizaje automático, minerÃa de datos, recuperación y gestión de información, bioinformática/neuroinformática, modelos bioinspirados (incluidas redes neuronales, computación evolutiva e inteligencia de enjambre), agentes y sistemas inteligentes hÃbridos. , aplicaciones del mundo real de técnicas inteligentes e IA. Nota de contenido: Orchids Classification Using Spatial Transformer Network with Adaptive Scaling -- Scalable Dictionary Classifiers for Time Series Classification -- Optimization of the numeric and categorical attribute weights in KAMILA mixed data clustering algorithm -- Meaningful Data Sampling for a Faithful Local Explanation Method -- Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor -- Adaptive Orthogonal Characteristics of Bio-inspired Neural Networks -- Using Deep Learning for Ordinal Classification of Mobile Marketing User Conversion -- Modeling Data Driven Interactions on Property Graph -- Adaptive Dimensionality Adjustment for Online "Principal Component Analysis" -- Relevance Metric for Counterfactuals Selection in Decision Trees -- Weighted Nearest Centroid Neighbourhood -- The Prevalence of Errors in Machine Learning Experiments -- A Hybrid Model for Fraud Detection on Purchase Orders -- Users Intention based on Twitter Features using Text Analytics -- Mixing hetero- and homogeneous models in weighted ensembles -- A Hybrid Approach to Time Series Classification with Shapelets -- An Ensemble Algorithm Based on Deep Learning for Tuberculosis Classification -- A Data-driven Approach to Automatic Extraction of Professional Figure Profiles from Résumés -- Retrieving and Processing Information from Clinical Algorithm via Formal Concept Analysis -- Comparative Analysis of Approaches to Building Medical Dialog Systems in Russian -- Tracking Position and Status of Electric Control Switches Based on YOLO Detector -- A Self-Generating Prototype method based on Information Entropy used for Condensing Data in Classification Tasks -- Transfer Knowledge between Sub-regions for Traffic Prediction using Deep Learning Method -- Global Q-Learning Approach for Power Allocation in Femtocell Networks -- Deep learning and Sensor Fusion Methods for Studying Gait Changes under Cognitive Load in Males and Females -- Towards a robotic personaltrainer for the elderly -- Image Quality Constrained GAN for Super-Resolution -- Use Case Prediction using Product Reviews Text Classification -- Convolutional Neural Network for Core Sections Identification in Scientific Research Publications -- Knowledge Inference Through Analysis of Human Activities -- Representation Learning of Knowledge Graphs with Multi-scale Capsule Network -- CNNPSP: Pseudouridine Sites Prediction Based on Deep Learning -- A Multimodal Approach to Image Sentiment Analysis -- Joining Items Clustering and Users Clustering for Evidential Collaborative Filtering -- Conditioned Generative Model via Latent Semantic Controlling for Learning Deep Representation of Data -- Toward A Framework for Seasonal Time Series Forecasting Using Clustering -- An Evidential Imprecise Answer Aggregation Approach based on Worker Clustering -- Combining Machine Learning and Classical Optimization Techniques in Vehicle to Vehicle Communication Network -- Adversarial Edit Attacks for Tree Data -- Non-stationary Noise Cancellation Using Deep Autoencoder based on Adversarial Learning -- A Deep Learning-based Surface Defect Inspection System for Smartphone Glass -- Superlinear Speedup of Parallel Population-based Metaheuristics: A Microservices and Container Virtualization Approach -- Active Dataset Generation for Meta-Learning System Quality Improvement -- Do You Really Follow Them? Automatic Detection of Credulous Twitter Users -- User Localization Based on Call Detail Record -- Automatic Ground Truth Dataset Creation for Fake News Detection in Social Media -- Artificial Flora Optimization Algorithm for Task Scheduling in Cloud Computing Environment -- A Significantly Faster Elastic-Ensemble for Time-Series Classification -- ALIME: Autoencoder Based Approach for Local Interpretability -- Detection of Abnormal Load Consumption in the Power Grid Using Clustering and Statistical Analysis -- Deep Convolutional Neural Networks Based on Image Data Augmentation for Visual Object Recognition -- An Efficient Scheme for Prototyping kNN in the Context of Real-Time Human Activity Recognition -- A Novel Recommendation System for Next Feature in Software -- Meta-learning Based Evolutionary Clustering Algorithm -- Fast tree-based classification via homogeneous clustering -- Ordinal equivalence classes for parallel coordinates -- New Internal Clustering Evaluation Index Based on Line Segments -- Threat Identification in Humanitarian Demining using Machine Learning and Spectroscopic Metal Detection. Tipo de medio : Computadora Summary : This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019. The 94 full papers presented were carefully reviewed and selected from 149 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2019 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models (including neural networks, evolutionary computation and swarm intelligence), agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Intelligent Data Engineering and Automated Learning – IDEAL 2019 : 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part II / Tipo de documento: documento electrónico Autores: Yin, Hujun, ; Camacho, David, ; Tino, Peter, ; Tallón-Ballesteros, Antonio J., ; Menezes, Ronaldo, ; Allmendinger, Richard, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2019 Número de páginas: XXI, 364 p. 115 ilustraciones, 86 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-33617-2 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: Inteligencia artificial IngenierÃa Informática y Redes Aplicaciones informáticas y de sistemas de información TeorÃa de la Computación Computadoras y Educación MinerÃa de datos y descubrimiento de conocimientos Red informática IngenierÃa Informática Application software Informática Procesamiento de datos Educación Clasificación: 6.312 Resumen: Este conjunto de dos volúmenes de LNCS 11871 y 11872 constituye las actas de la 20.ª Conferencia Internacional sobre IngenierÃa de Datos Inteligentes y Aprendizaje Automatizado, IDEAL 2019, celebrada en Manchester, Reino Unido, en noviembre de 2019. Los 94 artÃculos completos presentados fueron cuidadosamente revisados. y seleccionado entre 149 presentaciones. Estos artÃculos proporcionaron una muestra oportuna de los últimos avances en ingenierÃa de datos y aprendizaje automático, desde metodologÃas, marcos y algoritmos hasta aplicaciones. Los temas centrales de IDEAL 2019 incluyen desafÃos de big data, aprendizaje automático, minerÃa de datos, recuperación y gestión de información, bioinformática/neuroinformática, modelos bioinspirados (incluidas redes neuronales, computación evolutiva e inteligencia de enjambre), agentes y sistemas inteligentes hÃbridos. , aplicaciones del mundo real de técnicas inteligentes e IA. Nota de contenido: Special Session on Fuzzy Systems and Intelligent Data Analysis -- Computational Generalization in Taxonomies Applied to: (1) Analyze Tendencies of Research and (2) Extend User Audiences -- Unsupervised Initialization of Archetypal Analysis and Proportional Membership Fuzzy Clustering -- Special Session on Machine Learning towards Smarter Multimodal Systems -- Multimodal Web Based Video Annotator with Real-Time Human Pose Estimation -- New Interfaces for Classifying Performance Gestures in Music -- Special Session on Data Selection in Machine Learning -- Classifying Ransomware Using Machine Learning Algorithms -- Artificial Neural Networks in Mathematical Mini-Games for Automatic Students Learning Styles Identification: A First Approach -- The Use of Uniï¬ed Activity Records to Predict Requests Made by Applications for External Services -- Fuzzy Clustering Approach to Data Selection for Computer Usage in Headache Disorders -- Multitemporal Aerial Image Registration Using Semantic Features -- Special Session on Machine Learning in Healthcare -- Brain Tumor Classification Using Principal Component Analysis and Kernel Support Vector Machine -- Modelling survival by machine learning methods in liver transplantation: application to the UNOS dataset -- Design and Development of an Automatic Blood Detection System for Capsule Endoscopy Images -- Comparative Analysis for Computer-Based Decision Support: Case Study of Knee Osteoarthritis -- A Clustering-Based Patient Grouper for Burn Care -- A comparative assessment of Feed-Forward and Convolutional Neural Networks for the classification of prostate lesions -- Special Session on Machine Learning in Automatic Control -- A Method based on Filter Bank Common Spatial Pattern for Multiclass Motor Imagery BCI -- Safe Deep Neural Network-driven Autonomous Vehicles Using Software Safety Cages -- Wave and viscous resistance estimation by NN -- Neural controller of UAVs with inertia variations -- Special Session on Financeand Data Mining -- A Metric Framework for quantifying Data Concentration -- Adaptive Machine Learning-Based Stock Prediction using Financial Time Series Technical Indicators -- Special Session on Knowledge Discovery from Data -- Exploiting Online Newspaper Articles Metadata for Profiling City Areas -- Modelling the Social Interactions in Ant Colony Optimization -- An Innovative Deep-Learning Algorithm for Supporting the Approximate Classication of Workloads in Big Data Environments -- Control-flow Business Process Summarization via Activity Contraction -- Classifying Flies Based on Reconstructed Audio Signals -- Studying the Evolution of the 'Circular Economy' Concept using Topic Modelling -- Mining Frequent Distributions in Time Series -- Time Series Display for Knowledge Discovery on Selective Laser Melting Machines -- Special Session on Machine Learning Algorithms for Hard Problems -- Using Prior Knowledge to Facilitate Computational Reading of Arabic Calligraphy -- SMOTE Algorithm Variations in Balancing Data Streams -- Multi-Class Text Complexity Evaluation via Deep Neural Networks -- Imbalance reduction techniques applied to ECG classification problem -- Machine Learning Methods for Fake News Classification -- A genetic-based ensemble learning applied to imbalanced data classification -- The feasibility of deep learning use for adversarial model extraction in the cybersecurity domain. Tipo de medio : Computadora Summary : This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019. The 94 full papers presented were carefully reviewed and selected from 149 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2019 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models (including neural networks, evolutionary computation and swarm intelligence), agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Intelligent Data Engineering and Automated Learning – IDEAL 2019 : 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part II / [documento electrónico] / Yin, Hujun, ; Camacho, David, ; Tino, Peter, ; Tallón-Ballesteros, Antonio J., ; Menezes, Ronaldo, ; Allmendinger, Richard, . - 1 ed. . - [s.l.] : Springer, 2019 . - XXI, 364 p. 115 ilustraciones, 86 ilustraciones en color.
ISBN : 978-3-030-33617-2
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: Inteligencia artificial IngenierÃa Informática y Redes Aplicaciones informáticas y de sistemas de información TeorÃa de la Computación Computadoras y Educación MinerÃa de datos y descubrimiento de conocimientos Red informática IngenierÃa Informática Application software Informática Procesamiento de datos Educación Clasificación: 6.312 Resumen: Este conjunto de dos volúmenes de LNCS 11871 y 11872 constituye las actas de la 20.ª Conferencia Internacional sobre IngenierÃa de Datos Inteligentes y Aprendizaje Automatizado, IDEAL 2019, celebrada en Manchester, Reino Unido, en noviembre de 2019. Los 94 artÃculos completos presentados fueron cuidadosamente revisados. y seleccionado entre 149 presentaciones. Estos artÃculos proporcionaron una muestra oportuna de los últimos avances en ingenierÃa de datos y aprendizaje automático, desde metodologÃas, marcos y algoritmos hasta aplicaciones. Los temas centrales de IDEAL 2019 incluyen desafÃos de big data, aprendizaje automático, minerÃa de datos, recuperación y gestión de información, bioinformática/neuroinformática, modelos bioinspirados (incluidas redes neuronales, computación evolutiva e inteligencia de enjambre), agentes y sistemas inteligentes hÃbridos. , aplicaciones del mundo real de técnicas inteligentes e IA. Nota de contenido: Special Session on Fuzzy Systems and Intelligent Data Analysis -- Computational Generalization in Taxonomies Applied to: (1) Analyze Tendencies of Research and (2) Extend User Audiences -- Unsupervised Initialization of Archetypal Analysis and Proportional Membership Fuzzy Clustering -- Special Session on Machine Learning towards Smarter Multimodal Systems -- Multimodal Web Based Video Annotator with Real-Time Human Pose Estimation -- New Interfaces for Classifying Performance Gestures in Music -- Special Session on Data Selection in Machine Learning -- Classifying Ransomware Using Machine Learning Algorithms -- Artificial Neural Networks in Mathematical Mini-Games for Automatic Students Learning Styles Identification: A First Approach -- The Use of Uniï¬ed Activity Records to Predict Requests Made by Applications for External Services -- Fuzzy Clustering Approach to Data Selection for Computer Usage in Headache Disorders -- Multitemporal Aerial Image Registration Using Semantic Features -- Special Session on Machine Learning in Healthcare -- Brain Tumor Classification Using Principal Component Analysis and Kernel Support Vector Machine -- Modelling survival by machine learning methods in liver transplantation: application to the UNOS dataset -- Design and Development of an Automatic Blood Detection System for Capsule Endoscopy Images -- Comparative Analysis for Computer-Based Decision Support: Case Study of Knee Osteoarthritis -- A Clustering-Based Patient Grouper for Burn Care -- A comparative assessment of Feed-Forward and Convolutional Neural Networks for the classification of prostate lesions -- Special Session on Machine Learning in Automatic Control -- A Method based on Filter Bank Common Spatial Pattern for Multiclass Motor Imagery BCI -- Safe Deep Neural Network-driven Autonomous Vehicles Using Software Safety Cages -- Wave and viscous resistance estimation by NN -- Neural controller of UAVs with inertia variations -- Special Session on Financeand Data Mining -- A Metric Framework for quantifying Data Concentration -- Adaptive Machine Learning-Based Stock Prediction using Financial Time Series Technical Indicators -- Special Session on Knowledge Discovery from Data -- Exploiting Online Newspaper Articles Metadata for Profiling City Areas -- Modelling the Social Interactions in Ant Colony Optimization -- An Innovative Deep-Learning Algorithm for Supporting the Approximate Classication of Workloads in Big Data Environments -- Control-flow Business Process Summarization via Activity Contraction -- Classifying Flies Based on Reconstructed Audio Signals -- Studying the Evolution of the 'Circular Economy' Concept using Topic Modelling -- Mining Frequent Distributions in Time Series -- Time Series Display for Knowledge Discovery on Selective Laser Melting Machines -- Special Session on Machine Learning Algorithms for Hard Problems -- Using Prior Knowledge to Facilitate Computational Reading of Arabic Calligraphy -- SMOTE Algorithm Variations in Balancing Data Streams -- Multi-Class Text Complexity Evaluation via Deep Neural Networks -- Imbalance reduction techniques applied to ECG classification problem -- Machine Learning Methods for Fake News Classification -- A genetic-based ensemble learning applied to imbalanced data classification -- The feasibility of deep learning use for adversarial model extraction in the cybersecurity domain. Tipo de medio : Computadora Summary : This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019. The 94 full papers presented were carefully reviewed and selected from 149 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2019 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models (including neural networks, evolutionary computation and swarm intelligence), agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Intelligent Data Engineering and Automated Learning – IDEAL 2021 : 22nd International Conference, IDEAL 2021, Manchester, UK, November 25–27, 2021, Proceedings / Tipo de documento: documento electrónico Autores: Yin, Hujun, ; Camacho, David, ; Tino, Peter, ; Allmendinger, Richard, ; Tallón-Ballesteros, Antonio J., ; Tang, Ke, ; Cho, Sung-Bae, ; Novais, Paulo, ; Nascimento, Susana, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2021 Número de páginas: XVIII, 649 p. 224 ilustraciones, 173 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-91608-4 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: Educación Visión por computador Computadoras y Educación IngenierÃa de software Aprendizaje automático MinerÃa de datos y descubrimiento de conocimientos Procesamiento de datos Clasificación: 6.312 Resumen: Este libro constituye las actas arbitradas de la 22.ª Conferencia Internacional sobre IngenierÃa de Datos Inteligentes y Aprendizaje Automatizado, IDEAL 2021, que tuvo lugar del 25 al 27 de noviembre de 2021. La conferencia estaba originalmente prevista para realizarse en Manchester, Reino Unido, pero se llevó a cabo virtualmente. debido a la pandemia de COVID-19. Los 61 artÃculos completos incluidos en este libro fueron cuidadosamente revisados ​​y seleccionados entre 85 envÃos. Se ocupan de temas emergentes y desafiantes en el análisis de datos inteligentes y los paradigmas y sistemas de aprendizaje automático asociados. Se celebraron sesiones especiales sobre agrupación para el aprendizaje automático interpretable; aprendizaje automático hacia sistemas multimodales más inteligentes; e inteligencia computacional para visión por computadora y procesamiento de imágenes. Nota de contenido: Main Track -- A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality -- A Parallel Variable Neighborhood Search for Solving Real-World Production-Scheduling Problems -- Inheritances of Orthogonality in the Bio-inspired Layered Networks -- A Neural Architecture for Detecting Identifier Renaming from Diff -- Spell Checker Application Based on Levenshtein Automaton -- Ensemble Synthetic Oversampling with Manhattan Distance for Unbalanced Hyperspectral Data -- AutoML technologies for the identification of sparse models -- A Hierarchical Multi-Label Classification of Multi-Resident Activities -- Fast and Optimal Planner for the Discrete Grid-Based Coverage Path-Planning Problem -- Plagiarism Detection by Usage of Encoplot and Transformers -- Drift Detection in Text Data with Document Embeddings -- Validation of Video Retrieval by Kappa Measure for Inter-Judge Agreement -- Multi Language Application of Previously Developed Transcripts Classifier -- A complexity measure for binary classification problems based on lost points -- Linear Concept Approximation for Multilingual Document Recommendation -- Unsupervised Detection of Solving Strategies for Competitive Programming -- Application of long short-term memory neural networks for electric arc furnace modelling -- An Empirical Study of the Impact of Field Features in Learning-to-rank Method -- An Optimized Evidential Artificial Immune Recognition System based on Genetic Algorithm -- New Arabic Medical Dataset for Diseases Classification -- Improving Maximum Likelihood Estimation using Marginalization and Black-Box Variational Inference -- A Deep Learning-Based Approach for Train Arrival Time Prediction -- A Hybrid Approach for Predicting Bitcoin Price using Bi-LSTM and Bi-RNN Based Neural Network -- DC-Deblur: A Dilated Convolutional Network for Single Image Deblurring -- Time-series in Hyper-parameter Initialization of Machine Learning Techniques -- Prediction of Maintenance Equipment Failures Using AutomatedMachine Learning -- Learning Inter-Lingual Document Representations via Concept Compression -- Mixture-based probabilistic graphical models for the partial label ranking problem -- From classification to visualization: a two way trip -- Neural Complexity Assessment: A Deep Learning Approach to Readability Classification for European Portuguese Corpora -- Countering misinformation through semantic-aware multilingual models -- Genetic and Ant Colony algorithms to solve the multi-TSP -- Explainable AI (XAI) in Healthcare – Opportunities, Gaps and Challenges and a New Way to Look the Problem Space -- End-to-End Deep Learning for Detecting Metastatic Breast Cancer in Axillary Lymph Node from Digital Pathology Images -- SFU-CE: Skyline Frequent-Utility Itemset Discovery Using the Cross-Entropy Method -- Evaluating Football Player Actions during Counterattacks -- An Intelligent Decision Support System for Production Planning in Garments Industry -- Learning Dynamic Connectivity with Residual-Attention Network for Autism Classification in 4D fMRI Brain Images -- "A Profile on Twitter Shadowban: an AI Ethics -- position paper on Free-Speech" -- Meta-Feature Extraction Strategies for Active Anomaly Detection -- An implementation of the "Guess who?" game using CLIP -- Directional Graph Transformer-based Control Flow Embedding for Malware Classification -- Violence Detection with Audio inside the Car -- Evaluating Uni-dimensional Convolutional Neural Networks to Forecast the Influent pH of Wastewater Treatment Plants -- LSTM neural network modeling of wind speed and correlation analysis of wind and waves -- Finding Local Explanations through Masking Models -- Wind Turbine Modelling based on Neural Networks: a First Approach -- Multi-Attribute Forecast of the Price in the Iberian Electricity Market -- Tracking the temporal-evolution of supernova bubbles in numerical simulations -- SOMiMS - Topographic Mapping in the Model Space -- Fair Regret Minimization Queries -- Chimera: A Hybrid Machine Learning-Driven Multi-Objective Design Space Exploration Tool for FPGA High-Level Synthesis -- Special Session on Clustering for Interpretable Machine Learning -- Detecting Communities in Feature-Rich Networks with a K-Means Method -- Meta-learning based feature selection for clustering -- ACHC: Associative Classifier based on Hierarchical Clustering -- Special Session on Machine Learning towards Smarter Multimodal Systems -- Multimodal Semi-supervised Bipolar Disorder Classification -- Developments on support vector machines for multiple-expert learning -- WalkingStreet: understanding human mobility phenomena through a mobile application -- Indoor Positioning System for Ubiquitous Computing Environments -- Special Session on Computational Intelligence for Computer Vision and Image Processing -- T Line and C Line Detection and Ratio Reading of the Ovulation Test Strip Based on Deep Learning -- Radar echo image prediction algorithm based on multi-scale encoding-decoding network. . Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021, which took place during November 25-27, 2021. The conference was originally planned to take place in Manchester, UK, but was held virtually due to the COVID-19 pandemic. The 61 full papers included in this book were carefully reviewed and selected from 85 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Intelligent Data Engineering and Automated Learning – IDEAL 2021 : 22nd International Conference, IDEAL 2021, Manchester, UK, November 25–27, 2021, Proceedings / [documento electrónico] / Yin, Hujun, ; Camacho, David, ; Tino, Peter, ; Allmendinger, Richard, ; Tallón-Ballesteros, Antonio J., ; Tang, Ke, ; Cho, Sung-Bae, ; Novais, Paulo, ; Nascimento, Susana, . - 1 ed. . - [s.l.] : Springer, 2021 . - XVIII, 649 p. 224 ilustraciones, 173 ilustraciones en color.
ISBN : 978-3-030-91608-4
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Idioma : Inglés (eng)
Palabras clave: Educación Visión por computador Computadoras y Educación IngenierÃa de software Aprendizaje automático MinerÃa de datos y descubrimiento de conocimientos Procesamiento de datos Clasificación: 6.312 Resumen: Este libro constituye las actas arbitradas de la 22.ª Conferencia Internacional sobre IngenierÃa de Datos Inteligentes y Aprendizaje Automatizado, IDEAL 2021, que tuvo lugar del 25 al 27 de noviembre de 2021. La conferencia estaba originalmente prevista para realizarse en Manchester, Reino Unido, pero se llevó a cabo virtualmente. debido a la pandemia de COVID-19. Los 61 artÃculos completos incluidos en este libro fueron cuidadosamente revisados ​​y seleccionados entre 85 envÃos. Se ocupan de temas emergentes y desafiantes en el análisis de datos inteligentes y los paradigmas y sistemas de aprendizaje automático asociados. Se celebraron sesiones especiales sobre agrupación para el aprendizaje automático interpretable; aprendizaje automático hacia sistemas multimodales más inteligentes; e inteligencia computacional para visión por computadora y procesamiento de imágenes. Nota de contenido: Main Track -- A Comparison of Machine Learning Approaches for Predicting In-Car Display Production Quality -- A Parallel Variable Neighborhood Search for Solving Real-World Production-Scheduling Problems -- Inheritances of Orthogonality in the Bio-inspired Layered Networks -- A Neural Architecture for Detecting Identifier Renaming from Diff -- Spell Checker Application Based on Levenshtein Automaton -- Ensemble Synthetic Oversampling with Manhattan Distance for Unbalanced Hyperspectral Data -- AutoML technologies for the identification of sparse models -- A Hierarchical Multi-Label Classification of Multi-Resident Activities -- Fast and Optimal Planner for the Discrete Grid-Based Coverage Path-Planning Problem -- Plagiarism Detection by Usage of Encoplot and Transformers -- Drift Detection in Text Data with Document Embeddings -- Validation of Video Retrieval by Kappa Measure for Inter-Judge Agreement -- Multi Language Application of Previously Developed Transcripts Classifier -- A complexity measure for binary classification problems based on lost points -- Linear Concept Approximation for Multilingual Document Recommendation -- Unsupervised Detection of Solving Strategies for Competitive Programming -- Application of long short-term memory neural networks for electric arc furnace modelling -- An Empirical Study of the Impact of Field Features in Learning-to-rank Method -- An Optimized Evidential Artificial Immune Recognition System based on Genetic Algorithm -- New Arabic Medical Dataset for Diseases Classification -- Improving Maximum Likelihood Estimation using Marginalization and Black-Box Variational Inference -- A Deep Learning-Based Approach for Train Arrival Time Prediction -- A Hybrid Approach for Predicting Bitcoin Price using Bi-LSTM and Bi-RNN Based Neural Network -- DC-Deblur: A Dilated Convolutional Network for Single Image Deblurring -- Time-series in Hyper-parameter Initialization of Machine Learning Techniques -- Prediction of Maintenance Equipment Failures Using AutomatedMachine Learning -- Learning Inter-Lingual Document Representations via Concept Compression -- Mixture-based probabilistic graphical models for the partial label ranking problem -- From classification to visualization: a two way trip -- Neural Complexity Assessment: A Deep Learning Approach to Readability Classification for European Portuguese Corpora -- Countering misinformation through semantic-aware multilingual models -- Genetic and Ant Colony algorithms to solve the multi-TSP -- Explainable AI (XAI) in Healthcare – Opportunities, Gaps and Challenges and a New Way to Look the Problem Space -- End-to-End Deep Learning for Detecting Metastatic Breast Cancer in Axillary Lymph Node from Digital Pathology Images -- SFU-CE: Skyline Frequent-Utility Itemset Discovery Using the Cross-Entropy Method -- Evaluating Football Player Actions during Counterattacks -- An Intelligent Decision Support System for Production Planning in Garments Industry -- Learning Dynamic Connectivity with Residual-Attention Network for Autism Classification in 4D fMRI Brain Images -- "A Profile on Twitter Shadowban: an AI Ethics -- position paper on Free-Speech" -- Meta-Feature Extraction Strategies for Active Anomaly Detection -- An implementation of the "Guess who?" game using CLIP -- Directional Graph Transformer-based Control Flow Embedding for Malware Classification -- Violence Detection with Audio inside the Car -- Evaluating Uni-dimensional Convolutional Neural Networks to Forecast the Influent pH of Wastewater Treatment Plants -- LSTM neural network modeling of wind speed and correlation analysis of wind and waves -- Finding Local Explanations through Masking Models -- Wind Turbine Modelling based on Neural Networks: a First Approach -- Multi-Attribute Forecast of the Price in the Iberian Electricity Market -- Tracking the temporal-evolution of supernova bubbles in numerical simulations -- SOMiMS - Topographic Mapping in the Model Space -- Fair Regret Minimization Queries -- Chimera: A Hybrid Machine Learning-Driven Multi-Objective Design Space Exploration Tool for FPGA High-Level Synthesis -- Special Session on Clustering for Interpretable Machine Learning -- Detecting Communities in Feature-Rich Networks with a K-Means Method -- Meta-learning based feature selection for clustering -- ACHC: Associative Classifier based on Hierarchical Clustering -- Special Session on Machine Learning towards Smarter Multimodal Systems -- Multimodal Semi-supervised Bipolar Disorder Classification -- Developments on support vector machines for multiple-expert learning -- WalkingStreet: understanding human mobility phenomena through a mobile application -- Indoor Positioning System for Ubiquitous Computing Environments -- Special Session on Computational Intelligence for Computer Vision and Image Processing -- T Line and C Line Detection and Ratio Reading of the Ovulation Test Strip Based on Deep Learning -- Radar echo image prediction algorithm based on multi-scale encoding-decoding network. . Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021, which took place during November 25-27, 2021. The conference was originally planned to take place in Manchester, UK, but was held virtually due to the COVID-19 pandemic. The 61 full papers included in this book were carefully reviewed and selected from 85 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
