Intelligent Data Engineering and Automated Learning – IDEAL 2022

Intelligent Data Engineering and Automated Learning – IDEAL 2022
Author: Hujun Yin
Publisher: Springer Nature
Total Pages: 564
Release: 2022-11-20
Genre: Computers
ISBN: 3031217535

This book constitutes the refereed proceedings of the 23rd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2022, which took place in Manchester, UK, during November 24-26, 2022. The 52 full papers included in this book were carefully reviewed and selected from 79 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.

Intelligent Data Engineering and Automated Learning – IDEAL 2023

Intelligent Data Engineering and Automated Learning – IDEAL 2023
Author: Paulo Quaresma
Publisher: Springer Nature
Total Pages: 561
Release: 2023-12-16
Genre: Computers
ISBN: 3031482328

This book constitutes the proceedings of the 24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023, held in Évora, Portugal, during November 22–24, 2023. The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from 77 submissions. IDEAL 2023 is focusing on big data challenges, machine learning, deep learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models, agents and hybrid intelligent systems, and real-world applications of intelligence techniques and AI. The papers are organized in the following topical sections: main track; special session on federated learning and (pre) aggregation in machine learning; special session on intelligent techniques for real-world applications of renewable energy and green transport; and special session on data selection in machine learning.

Intelligent Data Engineering and Automated Learning – IDEAL 2020

Intelligent Data Engineering and Automated Learning – IDEAL 2020
Author: Cesar Analide
Publisher: Springer Nature
Total Pages: 633
Release: 2020-10-29
Genre: Computers
ISBN: 3030623653

This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.* The 93 papers presented were carefully reviewed and selected from 134 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 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. * The conference was held virtually due to the COVID-19 pandemic.

Intelligent Data Engineering and Automated Learning – IDEAL 2021

Intelligent Data Engineering and Automated Learning – IDEAL 2021
Author: Hujun Yin
Publisher: Springer Nature
Total Pages: 663
Release: 2021-11-23
Genre: Computers
ISBN: 3030916081

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.

Intelligent Data Engineering and Automated Learning – IDEAL 2019

Intelligent Data Engineering and Automated Learning – IDEAL 2019
Author: Hujun Yin
Publisher: Springer Nature
Total Pages: 575
Release: 2019-11-07
Genre: Computers
ISBN: 3030336077

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.

Intelligent Data Engineering and Automated Learning - IDEAL 2009

Intelligent Data Engineering and Automated Learning - IDEAL 2009
Author: Emilio Corchado
Publisher: Springer Science & Business Media
Total Pages: 848
Release: 2009-09-07
Genre: Computers
ISBN: 3642043933

This book constitutes the refereed proceedings of the 10th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2009, held in Burgos, Sapin, in September 2009. The 100 revised full papers presented were carefully reviewed and selected from over 200 submissions for inclusion in the book. The papers are organized in topical sections on learning and information processing; data mining and information management; neuro-informatics, bio-informatics, and bio-inspired models; agents and hybrid systems; soft computing techniques in data mining; recent advances on swarm-based computing; intelligent computational techniques in medical image processing; advances on ensemble learning and information fursion; financial and business engineering (modeling and applications); MIR day 2009 - Burgos; and nature inspired models for industrial applications.

Intelligent Data Engineering and Automated Learning – IDEAL 2018

Intelligent Data Engineering and Automated Learning – IDEAL 2018
Author: Hujun Yin
Publisher: Springer
Total Pages: 890
Release: 2018-11-08
Genre: Computers
ISBN: 3030034933

This two-volume set LNCS 11314 and 11315 constitutes the thoroughly refereed conference proceedings of the 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, held in Madrid, Spain, in November 2018. The 125 full papers presented were carefully reviewed and selected from 204 submissions. These papers provided a timely sample of the latest advances in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis.

Intelligent Systems and Pattern Recognition

Intelligent Systems and Pattern Recognition
Author: Akram Bennour
Publisher: Springer Nature
Total Pages: 333
Release: 2023-12-06
Genre: Computers
ISBN: 3031463382

This volume constitutes selected papers presented during the Third International Conference on Intelligent Systems and Pattern Recognition, ISPR 2023, held in Hammamet, Tunisia, in May 2023. The 44 full papers presented were thoroughly reviewed and selected from the 129 submissions. The papers are organized in the following topical sections: computer vision; data mining; pattern recognition; machine and deep learning.

Internet of Things-Based Machine Learning in Healthcare

Internet of Things-Based Machine Learning in Healthcare
Author: Prasenjit Dey
Publisher: CRC Press
Total Pages: 242
Release: 2024-06-10
Genre: Computers
ISBN: 1040031854

The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems. Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health records Focuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systems Showcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare services Discusses unsupervised genetic algorithm-based automatic heart disease prediction Covers Internet of Things–based hardware mechanisms and machine learning algorithms to predict the stress level of patients The text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology.