Frederic Stahl – författare

This book constitutes the proceedings of the 42nd SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2022, which was held in Cambridge, UK, in December 2022.The 20 full papers and 11 short papers presented in this volume were carefully reviewed and selected from 40 submissions.

This book constitutes the refereed proceedings of the 43rd SGAI International Conference on Artificial Intelligence, AI 2023, held in Cambridge, UK, during December 12–14, 2023. The 27 full papers and 20 short papers included in this book are carefully reviewed and selected from 67 submissions.

This two-volume set, LNAI 15446 and LNAI 15447, constitutes the refereed proceedings of the 44th SGAI International Conference on Artificial Intelligence, AI 2024, held in Cambridge, UK, during December 17–19, 2024.The 36 full papers and 18 short papers presented in these two volumes were carefully reviewed and selected from 80 submissions. Part I includes papers from the Technical stream, whereas Part II includes papers from the Application stream. These volumes are organized into the following topical sections: - Part I: Neural nets; Deep learning; Large language models; Machine learning; Evolutionary and genetic algorithms; Knowledge management, Short Technical Papers.Part II: Machine vision; Evaluation of AI systems; Applications of machine learning; Other AI applications, Short Application Papers.

This two-volume set, LNAI 15446 and LNAI 15447, constitutes the refereed proceedings of the 44th SGAI International Conference on Artificial Intelligence, AI 2024, held in Cambridge, UK, during December 17–19, 2024.The 36 full papers and 18 short papers presented in these two volumes were carefully reviewed and selected from 80 submissions. Part I includes papers from the Technical stream, whereas Part II includes papers from the Application stream. These volumes are organized into the following topical sections: - Part I: Neural nets; Deep learning; Large language models; Machine learning; Evolutionary and genetic algorithms; Knowledge management, Short Technical Papers.Part II: Machine vision; Evaluation of AI systems; Applications of machine learning; Other AI applications, Short Application Papers.

This two-volume set, LNAI 16301 and LNAI 16302, constitutes the refereed proceedings of the 45th SGAI International Conference on Artificial Intelligence, AI 2025, held in Cambridge, UK, during December 16-18, 2025.The 47 full papers and 20 short papers presented in these two volumes were carefully reviewed and selected from 93 submissions. The papers are grouped into these topical sections: Part I: Technical Papers; Deep Learning; Large Language Models; Machine Learning; Neural Networks; Techniques of AI and Short Technical Papers.Part II: Application Papers; Evolutionary Algorithms; Machine Learning; Neural Networks; Medical Computing and Health Informatics; Large Language Models; Natural Language Processing and Machine Vision; Applications of Artificial Intelligence and Short Application Papers.

This two-volume set, LNAI 16301 and LNAI 16302, constitutes the refereed proceedings of the 45th SGAI International Conference on Artificial Intelligence, AI 2025, held in Cambridge, UK, during December 16-18, 2025.The 47 full papers and 20 short papers presented in these two volumes were carefully reviewed and selected from 93 submissions. The papers are grouped into these topical sections: Part I: Technical Papers; Deep Learning; Large Language Models; Machine Learning; Neural Networks; Techniques of AI and Short Technical Papers.Part II: Application Papers; Evolutionary Algorithms; Machine Learning; Neural Networks; Medical Computing and Health Informatics; Large Language Models; Natural Language Processing and Machine Vision; Applications of Artificial Intelligence and Short Application Papers.

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.

The selected contributions covered cutting-edge aspects of Cloud Computing and Internet of Things, sensor networks, parallel and distributed computing, advanced networking, smart cities and smart buildings, Big Data and social networks.