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Deep Learning: Theory, Architectures and Applications in Speech, Image and Language Processing
This book is a detailed reference guide on deep learning and its applications. It aims to provide a basic understanding of deep learning and its different architectures that are applied to process images, speech, and natural language. It explains basic concepts and many modern use cases through fifteen chapters contributed by computer science academics and researchers. By the end of the book, the reader will become familiar with different deep learning approaches and models, and understand how to implement various deep learning algorithms using multiple frameworks and libraries. This book is divided into three parts. The first part explains the basic operating understanding, history, evoluti...
Machine Learning, Image Processing, Network Security and Data Sciences
This book constitutes the refereed proceedings of the Third International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2021. The papers are organized according to the following topical sections: data science and big data; image processing and computer vision; machine learning and computational intelligence; network and cybersecurity. This book aims to develop an understanding of image processing, networks, and data modeling by using various machine learning algorithms for a wide range of real-world applications. In addition to providing basic principles of data processing, this book teaches standard models and algorithms for data and image analysis.
Emerging Research in Computing, Information, Communication and Applications
This book presents the proceedings of International Conference on Emerging Research in Computing, Information, Communication and Applications, ERCICA 2016. ERCICA provides an interdisciplinary forum for researchers, professional engineers and scientists, educators, and technologists to discuss, debate and promote research and technology in the upcoming areas of computing, information, communication and their applications. The book discusses these emerging research areas, providing a valuable resource for researchers and practicing engineers alike.
IoT Based Control Networks and Intelligent Systems
This book gathers selected papers presented at International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS 2022), organized by St. Joseph’s College of Engineering and Technology, Kottayam, Kerala, India, during July 1–2, 2022. The book covers state-of-the-art research insights on Internet of things (IoT) paradigm to access, manage, and control the objects/things/people working under various information systems and deployed under wide range of applications like smart cities, health care, industries, and smart homes.
Pervasive Computing and Social Networking
The book features original papers from International Conference on Pervasive Computing and Social Networking (ICPCSN 2022), organized by NSIT, Salem, India during 3 – 4 March 2022. It covers research works on conceptual, constructive, empirical, theoretical and practical implementations of pervasive computing and social networking methods for developing more novel ideas and innovations in the growing field of information and communication technologies.
Harnessing Quantum Cryptography for Next-Generation Security Solutions
In an era where the escalating power of computers threatens the integrity of modern cryptographic systems, the need for stronger, more resilient security measures has never been more urgent. Quantum cryptography, with its solid theoretical foundation and increasingly mature practical implementations, offers a promising solution. From secure key distribution and direct communications to large prime factorization, quantum cryptography is becoming the backbone of numerous critical applications, including e-commerce, e-governance, and the emerging quantum internet. As a result, this field is capturing the attention of computer scientists and security professionals worldwide. Harnessing Quantum C...
Machine Learning, Image Processing, Network Security and Data Sciences
This two-volume set (CCIS 1240-1241) constitutes the refereed proceedings of the Second International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2020, held in Silchar, India. Due to the COVID-19 pandemic the conference has been postponed to July 2020. The 79 full papers and 4 short papers were thoroughly reviewed and selected from 219 submissions. The papers are organized according to the following topical sections: data science and big data; image processing and computer vision; machine learning and computational intelligence; network and cyber security.
Cloud Security
Cloud computing is an indispensable part of the modern Information and Communication Technology (ICT) systems. Cloud computing services have proven to be of significant importance, and promote quickly deployable and scalable IT solutions with reduced infrastructure costs. However, utilization of cloud also raises concerns such as security, privacy, latency, and governance, that keep it from turning into the predominant option for critical frameworks. As such, there is an urgent need to identify these concerns and to address them. Cloud Security: Concepts, Applications and Perspectives is a comprehensive work with substantial technical details for introducing the state-of-the-art research and...
Data Science
This book targets an audience with a basic understanding of deep learning, its architectures, and its application in the multimedia domain. Background in machine learning is helpful in exploring various aspects of deep learning. Deep learning models have a major impact on multimedia research and raised the performance bar substantially in many of the standard evaluations. Moreover, new multi-modal challenges are tackled, which older systems would not have been able to handle. However, it is very difficult to comprehend, let alone guide, the process of learning in deep neural networks, there is an air of uncertainty about exactly what and how these networks learn. By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.
Machine Learning Hybridization and Optimization for Intelligent Applications
This book discusses state-of-the-art reviews of the existing machine learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation. Features: • Focuses on hybridization and optimization of machine learning techniques. • Reviews supervised, unsupervised, and reinforcement learning using...
