國立高雄大學圖資館 |

Language: English

Back

Fusion of machine learning paradigmstheory and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fusion of machine learning paradigmsedited 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.
Contained By:	Springer Nature eBook
Subject:	Machine learning.
Online resource:	https://doi.org/10.1007/978-3-031-22371-6
ISBN:	9783031223716$q(electronic bk.)

Fusion of machine learning paradigmstheory 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.24..

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$q(electronic bk.)

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

188639
Machine learning.

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

Dewey Class. No.: 006.31

Fusion of machine learning paradigmstheory and applications /
LDR:02909nmm a2200337 a 4500 001 640250
003 DE-He213
005 20230206083658.0
006 m d
007 cr nn 008maaau
008 231025s2023 sz s 0 eng d
020 $a 9783031223716$q(electronic bk.)
020 $a 9783031223709$q(paper)
024 7 $a 10.1007/978-3-031-22371-6 $2 doi
035 $a 978-3-031-22371-6
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5 $b .F87 2023
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .F993 2023
245 0 0 $a Fusion of machine learning paradigms $h [electronic resource] : $b theory and applications / $c edited by Ioannis K. Hatzilygeroudis, George A. Tsihrintzis, Lakhmi C. Jain.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2023.
300 $a xii, 193 p. : $b ill., digital ; $c 24 cm.
490 1 $a Intelligent systems reference library, $x 1868-4408 ; $v v. 236
505 0 $a Editorial Note -- Artificial Intelligence as Dual-Use Technology -- Diabetic Retinopathy Detection using Transfer and Reinforcement Learning with effective image preprocessing and data augmentation techniques.
520 $a 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.
650 0 $a Machine learning. $3 188639
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Data and Information Security. $3 913130
700 1 $a Hatzilygeroudis, Ioannis. $3 511682
700 1 $a Tsihrintzis, George A. $3 284081
700 1 $a Jain, L. C. $3 204479
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Intelligent systems reference library ; $v v.24. $3 558591
856 4 0 $u https://doi.org/10.1007/978-3-031-22371-6
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)