Shiguo Lian – författare

This book proposes practical application paradigms for deep neural networks, aiming to establish best practices for real-world implementation.

Over the past decade, deep neural networks have made significant progress. However, effectively applying these networks to solve various practical problems remains challenging, which has limited the widespread application of artificial intelligence. Artificial Intelligence Paradigms for Application Practice is the first to comprehensively address implementation paradigms for deep neural networks in practice. The authors begin by reviewing the development of artificial neural networks and provide a systematic introduction to the tasks, principles, and architectures of deep neural networks. They identify the practical limitations of deep neural networks and propose guidelines and strategies for successful implementation. The book then examines 14 representative applications in urban planning, industrial production, and transportation. For each case, the authors present a landing paradigm that effectively addresses practical challenges supported by illustrations, background information, related work, methods, experiments, and conclusions. The experimental results validate the effectiveness of the proposed implementation approaches.

The book will benefit researchers, engineers, undergraduate, and graduate students interested in artificial intelligence, deep neural networks, large models, stable diffusion models, video surveillance, smart cities, intelligent manufacturing, intelligent transportation, and other related areas.

This book proposes practical application paradigms for deep neural networks, aiming to establish best practices for real-world implementation.

Over the past decade, deep neural networks have made significant progress. However, effectively applying these networks to solve various practical problems remains challenging, which has limited the widespread application of artificial intelligence. Artificial Intelligence Paradigms for Application Practice is the first to comprehensively address implementation paradigms for deep neural networks in practice. The authors begin by reviewing the development of artificial neural networks and provide a systematic introduction to the tasks, principles, and architectures of deep neural networks. They identify the practical limitations of deep neural networks and propose guidelines and strategies for successful implementation. The book then examines 14 representative applications in urban planning, industrial production, and transportation. For each case, the authors present a landing paradigm that effectively addresses practical challenges supported by illustrations, background information, related work, methods, experiments, and conclusions. The experimental results validate the effectiveness of the proposed implementation approaches.

The book will benefit researchers, engineers, undergraduate, and graduate students interested in artificial intelligence, deep neural networks, large models, stable diffusion models, video surveillance, smart cities, intelligent manufacturing, intelligent transportation, and other related areas.

MobiSec 2009 was the first ICST conference on security and privacy in mobile information and communication systems. With the the vast area of mobile technology research and application, the intention behind the creation of MobiSec was to make a small, but unique contribution to build a bridge between top-level research and large scale application of novel kinds of information security for mobile devices and communication.

The papers at MobiSec 2009 dealt with a broad variety of subjects ranging from issues of trust in and security of mobile devices and embedded hardware security, over efficient cryptography for resource-restricted platforms, to advanced applications such as wireless sensor networks, user authentication, and privacy in an environment of autonomously communicating objects. With hindsight a leitmotif emerged from these contributions, which corrobarated the idea behind MobiSec; a set of powerful tools have been created in various branches of the security discipline, which await combined application to build trust and security into mobile (that is, all future) networks, autonomous and personal devices, and pervasive applications

Multimedia data are used more and more widely in human being''s life, e.g., videoconferencing, visual telephone, IPTV, etc. Nearly most of the applications need multimedia transmission techniques that send multimedia data from one side to another side and keep the properties of efficiency, robustness and security. Here, the efficiency denotes the time cost of transmission operations, the robustness denotes the ability to survive transmission errors or noises, and the security denotes the protection of the transmitted media content. Recently, various intelligent or innovative techniques are invented, which bring vast performance improvements to practical applications. For example, such content transmission techniques as p2p, sensor network and ad hoc network are constructed, which adaptively use the peers’ properties to improve the network’s resources. Multimedia adaptation techniques can adjust the multimedia data rate in order to compliant with the network’s bandwidth. Scalable encryption techniques can generate the data stream that can be correctly decrypted after bit rate conversion. Ubiquitous multimedia services make the user share any kind of content anywhere.

The book includes fourteen chapters highlighting current concepts, issues and emerging technologies. Distinguished scholars from many prominent research institutions around the world contribute to the book. The book covers various aspects, including not only some fundamental knowledge and the latest key techniques, but also typical applications and open issues. For example, the covered topics include the present and future video coding standards, stereo and multiview coding techniques, free-viewpoint TV techniques, wireless broadcasting techniques, media streaming techniques, wireless media transmission techniques and systems, and User-Generated Content sharing.

Chaos-based cryptography, attracting many researchers in the past decade, is a research field across two fields, i.e., chaos (nonlinear dynamic system) and cryptography (computer and data security). It Chaos'' properties, such as randomness and ergodicity, have been proved to be suitable for designing the means for data protection.

The book gives a thorough description of chaos-based cryptography, which consists of chaos basic theory, chaos properties suitable for cryptography, chaos-based cryptographic techniques, and various secure applications based on chaos. Additionally, it covers both the latest research results and some open issues or hot topics.

The book creates a collection of high-quality chapters contributed by leading experts in the related fields. It embraces a wide variety of aspects of the related subject areas and provide a scientifically and scholarly sound treatment of state-of-the-art techniques to students, researchers, academics, personnel of law enforcement and IT practitioners who are interested or involved in the study, research, use, design and development of techniques related to chaos-based cryptography.