國立虎尾科技大學 |

Data science in applications = towards AI-driven approaches /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data science in applications/ edited by Gintautas Dzemyda, Jolita Bernatavičienė, Janusz Kacprzyk.
其他題名:	towards AI-driven approaches /
其他作者:	Dzemyda, Gintautas.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xii, 302 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Data mining - Industrial applications. -
電子資源:	https://doi.org/10.1007/978-3-031-88486-3
ISBN:	9783031884863

Data science in applications = towards AI-driven approaches /
Data science in applicationstowards AI-driven approaches /[electronic resource] :edited by Gintautas Dzemyda, Jolita Bernatavičienė, Janusz Kacprzyk. - Cham :Springer Nature Switzerland :2025. - xii, 302 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v. 12061860-9503 ;. - Studies in computational intelligence ;v. 50. .

Part1.AI-supported multimedia systems -- 1.Automated Actor Recognition in Video Content -- 2.Acquiring Knowledge for Mimicking Dysarthric Speech by Incorporating its Features into Synthetic Speech -- 3.Monolingual and Cross-Lingual Text Classification -- 4.Towards Text Simplification for Lithuanian -- 5.Selection of preprocessing parameters for Wave-U-Net-based speech-denoising -- 6.Application of AI-based methods in the study of textual historical sources and urban heritage landscapes -- Part2.AI-supported multimedia systems -- 7.A Review of Quantum Machine Learning Applications -- 8.Class imbalance and data splitting approaches for face image pain classification: survey and experimental comparisons -- 9.Commit Classification for Software Change Intention Categorization Through Multimodal Machine Learning -- 10.AI for Earth Observation -- 11.Generative approach to supervised classification of spatio-temporal data via continuous observation Hidden Markov Model -- 12."Deformed solitary solutions to nonlinear differential equations based on the AI-assisted generalized operator of differentiation".

This book provides a forum for presenting and discussing new and promising ideas in the broadly understood data science field and scope. Data science is a broad discipline. Related and partially overlapping fields are data mining, pattern recognition, neurocomputing, statistics, mathematics, data visualisation, databases, data processing, knowledge discovery in databases, big data analysis, computer science, cloud computing, machine learning, and artificial intelligence. Recent research has focused on unlocking the new possibilities of artificial intelligence, not only from a theoretical point of view but also from an applied perspective. In light of recent developments and trends in these fields, the topics covered in the book have been expanded and extended to include various aspects of artificial intelligence (AI), advanced data analysis, data analytics, machine learning, and multimedia, both from a theoretical and a practical application perspective. All of these are coming together, so we are seeing a variety of AI-driven approaches. This book contains 12 chapters by data science researchers. They are divided into "AI-supported multimedia systems" and "Developments, challenges, and applications of advanced data analysis and machine learning." The first part of the book contains chapters that discuss various aspects of multimedia systems, notably text, voice, and image, in particular from the point of view of how new developments in AI, advanced data analyses, etc., can provide new, effective and efficient, tools and techniques, maybe even imply research and implementation breakthroughs. The second part of the book, "Developments, challenges and applications of advanced data analysis and machine learning," is concerned with various aspects, problems, solutions, and applications for new sophisticated tools and techniques of data analyses, data analytics, and machine learning providing tools and techniques to take advantage of what is available in data.

ISBN: 9783031884863

Standard No.: 10.1007/978-3-031-88486-3doiSubjects--Topical Terms:

1229962
Data mining
--Industrial applications.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

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520 $a This book provides a forum for presenting and discussing new and promising ideas in the broadly understood data science field and scope. Data science is a broad discipline. Related and partially overlapping fields are data mining, pattern recognition, neurocomputing, statistics, mathematics, data visualisation, databases, data processing, knowledge discovery in databases, big data analysis, computer science, cloud computing, machine learning, and artificial intelligence. Recent research has focused on unlocking the new possibilities of artificial intelligence, not only from a theoretical point of view but also from an applied perspective. In light of recent developments and trends in these fields, the topics covered in the book have been expanded and extended to include various aspects of artificial intelligence (AI), advanced data analysis, data analytics, machine learning, and multimedia, both from a theoretical and a practical application perspective. All of these are coming together, so we are seeing a variety of AI-driven approaches. This book contains 12 chapters by data science researchers. They are divided into "AI-supported multimedia systems" and "Developments, challenges, and applications of advanced data analysis and machine learning." The first part of the book contains chapters that discuss various aspects of multimedia systems, notably text, voice, and image, in particular from the point of view of how new developments in AI, advanced data analyses, etc., can provide new, effective and efficient, tools and techniques, maybe even imply research and implementation breakthroughs. The second part of the book, "Developments, challenges and applications of advanced data analysis and machine learning," is concerned with various aspects, problems, solutions, and applications for new sophisticated tools and techniques of data analyses, data analytics, and machine learning providing tools and techniques to take advantage of what is available in data.
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