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Practical Data Mining Techniques and Applications
Data mining techniques and algorithms are extensively used to build real-world applications. A practical approach can be applied to data mining techniques to build applications. Once deployed, an application enables the developers to work on the users’ goals and mold the algorithms with respect to users’ perspectives. Practical Data Mining Techniques and Applications focuses on various concepts related to data mining and how these techniques can be used to develop and deploy applications. The book provides a systematic composition of fundamental concepts of data mining blended with practical applications. The aim of this book is to provide access to practical data mining applications and...
Computer Vision – ECCV 2020
The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Next Generation Multiple Access
Highly comprehensive resource investigating how next-generation multiple access (NGMA) relates to unrestricted global connection, business requirements, and sustainable wireless networks Next Generation Multiple Access is a comprehensive, state-of-the-art, and approachable guide to the fundamentals and applications of next-generation multiple access (NGMA) schemes, guiding the future development of industries, government requirements, and military utilization of multiple access systems for wireless communication systems and providing various application scenarios to fit practical case studies. The scope and depth of this book are balanced for both beginners to advanced users. Additional refe...
Federated Learning
Federated Learning: Theory and Practi ce provides a holisti c treatment to federated learning as a distributed learning system with various forms of decentralized data and features. Part I of the book begins with a broad overview of opti mizati on fundamentals and modeling challenges, covering various aspects of communicati on effi ciency, theoretical convergence, and security. Part II featuresemerging challenges stemming from many socially driven concerns of federated learning as a future public machine learning service. Part III concludes the book with a wide array of industrial applicati ons of federated learning, as well as ethical considerations, showcasing its immense potential for dri...
Metaverse Communication and Computing Networks
Metaverse Communication and Computing Networks Understand the future of the Internet with this wide-ranging analysis “Metaverse” is the term for applications that allow users to assume digital avatars to interact with other humans and software functions in a three-dimensional virtual space. These applications and the spaces they create constitute an exciting and challenging new frontier in digital communication. Surmounting the technological and conceptual barriers to creating the Metaverse will require researchers and engineers familiar with its underlying theories and a wide range of technologies and techniques. Metaverse Communication and Computing Networks provides a comprehensive tr...
AI, Machine Learning and Deep Learning
Today, Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society, many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices, they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, among many other attacks and threats. Such attacks can make AI products dangerous to use. While this discussion focuses on ...
Large Language Models in Cybersecurity
This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful large language models (LLMs) and how they can be mitigated. It attempts to outrun the malicious attackers by anticipating what they could do. It also alerts LLM developers to understand their work's risks for cybersecurity and provides them with tools to mitigate those risks. The book starts in Part I with a general introduction to LLMs and their main application areas. Part II collects a description of the most salient threats LLMs represent in cybersecurity, be they as tools for cybercriminals or as novel attack surfaces if integrated into e...
