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Intelligent Data Engineering and Automated Learning – IDEAL 2019

20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part II

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Hujun Yin

    1. University of Manchester, Manchester, UK

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  2. David Camacho

    1. Technical University of Madrid, Madrid, Spain

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  3. Peter Tino

    1. University of Birmingham, Birmingham, UK

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  4. Antonio J. Tallón-Ballesteros

    1. University of Huelva, Huelva, Spain

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  5. Ronaldo Menezes

    1. University of Exeter, Exeter, UK

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  6. Richard Allmendinger

    1. University of Manchester, Manchester, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11872)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: IDEAL 2019.

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Table of contents (36 papers)

  1. Front Matter

    Pages i-xxi
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  2. Special Session on Fuzzy Systems and Intelligent Data Analysis

    1. Front Matter

      Pages 1-1
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    2. Computational Generalization in Taxonomies Applied to: (1) Analyze Tendencies of Research and (2) Extend User Audiences

      • Dmitry Frolov, Susana Nascimento, Trevor Fenner, Zina Taran, Boris Mirkin
      Pages 3-11

    3. Unsupervised Initialization of Archetypal Analysis and Proportional Membership Fuzzy Clustering

      • Susana Nascimento, Nuno Madaleno
      Pages 12-20

  3. Special Session on Machine Learning Towards Smarter Multimodal Systems

    1. Front Matter

      Pages 21-21
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    2. Multimodal Web Based Video Annotator with Real-Time Human Pose Estimation

      • Rui Rodrigues, Rui Neves Madeira, Nuno Correia, Carla Fernandes, Sara Ribeiro
      Pages 23-30

    3. New Interfaces for Classifying Performance Gestures in Music

      • Chris Rhodes, Richard Allmendinger, Ricardo Climent
      Pages 31-42

  4. Special Session on Data Selection in Machine Learning

    1. Front Matter

      Pages 43-43
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    2. Classifying Ransomware Using Machine Learning Algorithms

      • Samuel Egunjobi, Simon Parkinson, Andrew Crampton
      Pages 45-52

    3. Artificial Neural Networks in Mathematical Mini-Games for Automatic Students’ Learning Styles Identification: A First Approach

      • Richard Torres-Molina, Jorge Banda-Almeida, Lorena Guachi-Guachi
      Pages 53-60

    4. The Use of Unified Activity Records to Predict Requests Made by Applications for External Services

      • Maciej Grzenda, Robert Kunicki, Jaroslaw Legierski
      Pages 61-69

    5. Fuzzy Clustering Approach to Data Selection for Computer Usage in Headache Disorders

      • Svetlana Simić, Ljiljana Radmilo, Dragan Simić, Svetislav D. Simić, Antonio J. Tallón-Ballesteros
      Pages 70-77

    6. Multitemporal Aerial Image Registration Using Semantic Features

      • Ananya Gupta, Yao Peng, Simon Watson, Hujun Yin
      Pages 78-86

  5. Special Session on Machine Learning in Healthcare

    1. Front Matter

      Pages 87-87
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    2. Brain Tumor Classification Using Principal Component Analysis and Kernel Support Vector Machine

      • Richard Torres-Molina, Carlos Bustamante-Orellana, Andrés Riofrío-Valdivieso, Francisco Quinga-Socasi, Robinson Guachi, Lorena Guachi-Guachi
      Pages 89-96

    3. Modelling Survival by Machine Learning Methods in Liver Transplantation: Application to the UNOS Dataset

      • David Guijo-Rubio, Pedro J. Villalón-Vaquero, Pedro A. Gutiérrez, Maria Dolores Ayllón, Javier Briceño, César Hervás-Martínez
      Pages 97-104

    4. Design and Development of an Automatic Blood Detection System for Capsule Endoscopy Images

      • Pedro Pons, Reinier Noorda, Andrea Nevárez, Adrián Colomer, Vicente Pons Beltrán, Valery Naranjo
      Pages 105-113

    5. Comparative Analysis for Computer-Based Decision Support: Case Study of Knee Osteoarthritis

      • Philippa Grace McCabe, Ivan Olier, Sandra Ortega-Martorell, Ian Jarman, Vasilios Baltzopoulos, Paulo Lisboa
      Pages 114-122

    6. A Clustering-Based Patient Grouper for Burn Care

      • Chimdimma Noelyn Onah, Richard Allmendinger, Julia Handl, Paraskevas Yiapanis, Ken W. Dunn
      Pages 123-131

    7. A Comparative Assessment of Feed-Forward and Convolutional Neural Networks for the Classification of Prostate Lesions

      • Sabrina Marnell, Patrick Riley, Ivan Olier, Marc Rea, Sandra Ortega-Martorell
      Pages 132-138
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Other volumes

  1. Intelligent Data Engineering and Automated Learning – IDEAL 2019

  2. Intelligent Data Engineering and Automated Learning – IDEAL 2019

Keywords

About this book

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.

Editors and Affiliations

  • University of Manchester, Manchester, UK

    Hujun Yin, Richard Allmendinger

  • Technical University of Madrid, Madrid, Spain

    David Camacho

  • University of Birmingham, Birmingham, UK

    Peter Tino

  • University of Huelva, Huelva, Spain

    Antonio J. Tallón-Ballesteros

  • University of Exeter, Exeter, UK

    Ronaldo Menezes

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