Bøger af George A. Tsihrintzis

This book presents selected papers from the 17th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, in conjunction with the 14th International Conference on Frontiers of Information Technology, Applications and Tools, held on 29-31 October 2021 in Kaohsiung, Taiwan. It is divided into two volumes and discusses latest research outcomes in the field of information technology (IT) including but not limited to information hiding, multimedia signal processing, big data, data mining, bioinformatics, database, industrial and internet of things, and their applications.

This book aims to attract researchers and practitioners who are working in information technology and computer science. This edited book is about basics and high-level concepts regarding blockchain technology and application, multimedia security, information processing, security of network, cloud and IoT, cryptography and information hiding, cyber-security and evidence investigations, and learning and intelligent computing. It is becoming increasingly important to develop adaptive, intelligent computing-centric, energy-aware, secure, and privacy-aware mechanisms in high-performance computing and IoT applications. The book serves as a useful guide for industry persons and also helps beginners to learn things from basic to advance in the area of better computing paradigm. Our aim is intended to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results in security-related areas. We believe that this book not only presents novel and interesting ideas but also will stimulate interesting discussions from the participants and inspire new ideas.

The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine learning systems.

This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes.