Data Science in Applications : Towards AI-Driven Approaches / / edited by Gintautas Dzemyda, Jolita Bernatavičienė, Janusz Kacprzyk

• Autore: Dzemyda Gintautas
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025
• Edizione: 1st ed. 2025.
• Descrizione fisica: 1 online resource (403 pages)
• Disciplina: 006.312
• Soggetto topico: Computational intelligence; Engineering - Data processing; Artificial intelligence; Computational Intelligence; Data Engineering; Artificial Intelligence
• Altri autori: BernatavicieneJolita KacprzykJanusz
• Nota di contenuto: 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".
• Sommario/riassunto: 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.
• Titolo autorizzato: Data Science in Applications
• ISBN: 3-031-88486-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911021959703321
• Lo trovi qui: Univ. Federico II
• Serie: Studies in Computational Intelligence, . 1860-9503 ; ; 1206