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Fusion of machine learning paradigms...

Hatzilygeroudis, Ioannis.

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Fusion of machine learning paradigms = theory and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fusion of machine learning paradigms/ edited by Ioannis K. Hatzilygeroudis, George A. Tsihrintzis, Lakhmi C. Jain.
Reminder of title:	theory and applications /
other author:	Hatzilygeroudis, Ioannis.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	xii, 193 p. :ill., digital ;24 cm.
[NT 15003449]:	Editorial Note -- Artificial Intelligence as Dual-Use Technology -- Diabetic Retinopathy Detection using Transfer and Reinforcement Learning with effective image preprocessing and data augmentation techniques.
Contained By:	Springer Nature eBook
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-3-031-22371-6
ISBN:	9783031223716

Fusion of machine learning paradigms = theory and applications /
Fusion of machine learning paradigmstheory and applications /[electronic resource] :edited by Ioannis K. Hatzilygeroudis, George A. Tsihrintzis, Lakhmi C. Jain. - Cham :Springer International Publishing :2023. - xii, 193 p. :ill., digital ;24 cm. - Intelligent systems reference library,v. 2361868-4408 ;. - Intelligent systems reference library ;v. 236..

Editorial Note -- Artificial Intelligence as Dual-Use Technology -- Diabetic Retinopathy Detection using Transfer and Reinforcement Learning with effective image preprocessing and data augmentation techniques.

This book aims at updating the relevant computer science-related research communities, including professors, researchers, scientists, engineers and students, as well as the general reader from other disciplines, on the most recent advances in applications of methods based on Fusing Machine Learning Paradigms. Integrated or Hybrid Machine Learning methodologies combine together two or more Machine Learning approaches achieving higher performance and better efficiency when compared to those of their constituent components and promising major impact in science, technology and the society. The book consists of an editorial note and an additional eight chapters and is organized into two parts, namely: (i) Recent Application Areas of Fusion of Machine Learning Paradigms and (ii) Applications that can clearly benefit from Fusion of Machine Learning Paradigms. This book is directed toward professors, researchers, scientists, engineers and students in Machine Learning-related disciplines, as the hybridism presented, and the case studies described provide researchers with successful approaches and initiatives to efficiently address complex classification or regression problems. It is also directed toward readers who come from other disciplines, including Engineering, Medicine or Education Sciences, and are interested in becoming versed in some of the most recent Machine Learning-based technologies. Extensive lists of bibliographic references at the end of each chapter guide the readers to probe further into the application areas of interest to them.

ISBN: 9783031223716

Standard No.: 10.1007/978-3-031-22371-6doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .F87 2023

Dewey Class. No.: 006.31

Fusion of machine learning paradigms = theory and applications /
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