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Analog and Digital Communication
An introductory course on analog and digital communications is fundamental to the undergraduate program in electrical engineering. This course is usually offered at the junior level. Typically, it is assumed that the student has a background in calculus, electronics, signals and systems, and possibly probability theory. Bearing in mind the introductory nature of this course, a textbook recommended for the course must be easy to read, accurate, and contain an abundance of insightful examples, problems, and computer experiments. These objectives of the book are needed to expedite learning the fundamentals of communication systems at an introductory level and in an effective manner. This book h...
Deep Learning in Healthcare
This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.
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.
Pattern Recognition and Machine Learning
This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.
Productivity in Construction Projects
PRODUCTIVITY IN CONSTRUCTION PROJECTS From planning/design to post-construction, this valuable guide provides the construction industry the key to understanding the importance of properly tracking and measuring productivity, resulting in increased efficiency and profitability for contractors, subcontractors, owners, civil and construction engineers, and attorneys. Productivity in Construction Projects anticipates and answers the questions of owners, contractors, sub-contractors, and construction professionals to avoid cost overruns in a specific area of work, or when activities are taking more resources to perform than planned. Packed with real-world case studies, Productivity in Constructio...
Glioblastoma:
Glioblastoma is the most malignant brain tumor that still remains incurable. It is such a deadly disease that patients do not survive more than a few months after diagnosis. Our understanding of the histopathology and molecular mechanisms of formation of glioblastoma is rapidly advancing so as to provide us clues for devising rational therapeutic strategies for treatment of this malignancy. It is important that we continue to improve our knowledge about the pathogenesis of this devastating disease and explore new areas to find successful therapeutic strategies. Various approaches such as sophisticated imaging techniques, improved surgical procedures, ground-breaking strategies for radiotherapy, chemotherapy, immunotherapy, chemoimmunotherapy, and photodynamic therapy are being used for eradicating glioblastoma. Hopefully, this book will be an important source of information on glioblastoma and therefore be highly useful to the students, postdoctoral fellows, principal investigators, and clinicians involved in this field.
Decision Forests
Presents a unified, efficient model of random decision forests which can be used in a number of applications such as scene recognition from photographs, object recognition in images, automatic diagnosis from radiological scans and document analysis.
Introduction to Biometrics
Biometric recognition, or simply biometrics, is the science of establishing the identity of a person based on physical or behavioral attributes. It is a rapidly evolving field with applications ranging from securely accessing one’s computer to gaining entry into a country. While the deployment of large-scale biometric systems in both commercial and government applications has increased the public awareness of this technology, "Introduction to Biometrics" is the first textbook to introduce the fundamentals of Biometrics to undergraduate/graduate students. The three commonly used modalities in the biometrics field, namely, fingerprint, face, and iris are covered in detail in this book. Few o...
Multilevel Inverters
Multilevel Inverters: Conventional and Emerging Topologies and Their Control is written with two primary objectives: (a) explanation of fundamentals of multilevel inverters (MLIs) with reference to the general philosophy of power electronics; and (b) enabling the reader to systematically analyze a given topology with the possibility of contributing towards the ongoing evolution of topologies. The authors also present an updated status of current research in the field of MLIs with an emphasis on the evolution of newer topologies. In addition, the work includes a universal control scheme, with which any given topology can be modulated. Extensive qualitative and quantitative evaluations of emer...
