Workshop On Neural Networks Techniques And Applications

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The Deep Learning Workshop

Author : Mirza Rahim Baig
Publisher : Packt Publishing Ltd
ISBN 13 : 1839210567
Total Pages : 473 pages
Book Rating : 4.8/5 (392 download)

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Book Synopsis The Deep Learning Workshop by : Mirza Rahim Baig

Download or read book The Deep Learning Workshop written by Mirza Rahim Baig and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text Key Features Understand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognition Study the architecture of different neural networks Book Description Are you fascinated by how deep learning powers intelligent applications such as self-driving cars, virtual assistants, facial recognition devices, and chatbots to process data and solve complex problems? Whether you are familiar with machine learning or are new to this domain, The Deep Learning Workshop will make it easy for you to understand deep learning with the help of interesting examples and exercises throughout. The book starts by highlighting the relationship between deep learning, machine learning, and artificial intelligence and helps you get comfortable with the TensorFlow 2.0 programming structure using hands-on exercises. You'll understand neural networks, the structure of a perceptron, and how to use TensorFlow to create and train models. The book will then let you explore the fundamentals of computer vision by performing image recognition exercises with convolutional neural networks (CNNs) using Keras. As you advance, you'll be able to make your model more powerful by implementing text embedding and sequencing the data using popular deep learning solutions. Finally, you'll get to grips with bidirectional recurrent neural networks (RNNs) and build generative adversarial networks (GANs) for image synthesis. By the end of this deep learning book, you'll have learned the skills essential for building deep learning models with TensorFlow and Keras. What you will learn Understand how deep learning, machine learning, and artificial intelligence are different Develop multilayer deep neural networks with TensorFlow Implement deep neural networks for multiclass classification using Keras Train CNN models for image recognition Handle sequence data and use it in conjunction with RNNs Build a GAN to generate high-quality synthesized images Who this book is for If you are interested in machine learning and want to create and train deep learning models using TensorFlow and Keras, this workshop is for you. A solid understanding of Python and its packages, along with basic machine learning concepts, will help you to learn the topics quickly.

Proceedings of the Workshop on Neural Network Applications and Tools, September 13-14, 1993, Liverpool, England

Author : Paulo J. G. Lisboa
Publisher :
ISBN 13 :
Total Pages : 166 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Proceedings of the Workshop on Neural Network Applications and Tools, September 13-14, 1993, Liverpool, England by : Paulo J. G. Lisboa

Download or read book Proceedings of the Workshop on Neural Network Applications and Tools, September 13-14, 1993, Liverpool, England written by Paulo J. G. Lisboa and published by . This book was released on 1994 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Engineering Applications of Neural Networks

Author : Giacomo Boracchi
Publisher : Springer
ISBN 13 : 3319651722
Total Pages : 739 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Engineering Applications of Neural Networks by : Giacomo Boracchi

Download or read book Engineering Applications of Neural Networks written by Giacomo Boracchi and published by Springer. This book was released on 2017-07-30 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 18th International Conference on Engineering Applications of Neural Networks, EANN 2017, held in Athens, Greece, in August 2017. The 40 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 83 submissions. The papers cover the topics of deep learning, convolutional neural networks, image processing, pattern recognition, recommendation systems, machine learning, and applications of Artificial Neural Networks (ANN) applications in engineering, 5G telecommunication networks, and audio signal processing. The volume also includes papers presented at the 6th Mining Humanistic Data Workshop (MHDW 2017) and the 2nd Workshop on 5G-Putting Intelligence to the Network Edge (5G-PINE).

The The Deep Learning with PyTorch Workshop

Author : Hyatt Saleh
Publisher : Packt Publishing Ltd
ISBN 13 : 1838981845
Total Pages : 329 pages
Book Rating : 4.8/5 (389 download)

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Book Synopsis The The Deep Learning with PyTorch Workshop by : Hyatt Saleh

Download or read book The The Deep Learning with PyTorch Workshop written by Hyatt Saleh and published by Packt Publishing Ltd. This book was released on 2020-07-22 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get a head start in the world of AI and deep learning by developing your skills with PyTorch Key FeaturesLearn how to define your own network architecture in deep learningImplement helpful methods to create and train a model using PyTorch syntaxDiscover how intelligent applications using features like image recognition and speech recognition really process your dataBook Description Want to get to grips with one of the most popular machine learning libraries for deep learning? The Deep Learning with PyTorch Workshop will help you do just that, jumpstarting your knowledge of using PyTorch for deep learning even if you’re starting from scratch. It's no surprise that deep learning's popularity has risen steeply in the past few years, thanks to intelligent applications such as self-driving vehicles, chatbots, and voice-activated assistants that are making our lives easier. This book will take you inside the world of deep learning, where you'll use PyTorch to understand the complexity of neural network architectures. The Deep Learning with PyTorch Workshop starts with an introduction to deep learning and its applications. You'll explore the syntax of PyTorch and learn how to define a network architecture and train a model. Next, you'll learn about three main neural network architectures - convolutional, artificial, and recurrent - and even solve real-world data problems using these networks. Later chapters will show you how to create a style transfer model to develop a new image from two images, before finally taking you through how RNNs store memory to solve key data issues. By the end of this book, you'll have mastered the essential concepts, tools, and libraries of PyTorch to develop your own deep neural networks and intelligent apps. What you will learnExplore the different applications of deep learningUnderstand the PyTorch approach to building neural networksCreate and train your very own perceptron using PyTorchSolve regression problems using artificial neural networks (ANNs)Handle computer vision problems with convolutional neural networks (CNNs)Perform language translation tasks using recurrent neural networks (RNNs)Who this book is for This deep learning book is ideal for anyone who wants to create and train deep learning models using PyTorch. A solid understanding of the Python programming language and its packages will help you grasp the topics covered in the book more quickly.

Neural Networks: Best Practice In Europe - Proceedings Of The Stichting Neurale Netwerken Conference 1997, Progre

Author : Bert Kappen
Publisher : World Scientific
ISBN 13 : 9814545376
Total Pages : 226 pages
Book Rating : 4.8/5 (145 download)

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Book Synopsis Neural Networks: Best Practice In Europe - Proceedings Of The Stichting Neurale Netwerken Conference 1997, Progre by : Bert Kappen

Download or read book Neural Networks: Best Practice In Europe - Proceedings Of The Stichting Neurale Netwerken Conference 1997, Progre written by Bert Kappen and published by World Scientific. This book was released on 1998-01-15 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: After the explosion of research on neural networks in the eighties, the nineties have seen a boom in industrial applications of neural networks. In contrast to the large output of publications in international neural network journals, which reflects the increase in neural network research, the large number of successful applications are less accessible. To make a survey of successful applications in industry in Europe, a project called SIENA was initiated with support from the European Community. The aim of SIENA was to assess the business impact of neural networks. Data were collected on both the supplier side and the end-user side of the market. In addition, case studies of successful 'money-making' applications using neural networks were gathered. This book contains detailed descriptions of some of the applications.

Efficient Processing of Deep Neural Networks

Author : Vivienne Sze
Publisher : Springer Nature
ISBN 13 : 3031017668
Total Pages : 254 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Efficient Processing of Deep Neural Networks by : Vivienne Sze

Download or read book Efficient Processing of Deep Neural Networks written by Vivienne Sze and published by Springer Nature. This book was released on 2022-05-31 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.

Workshops Proceedings of the 5th International Conference on Intelligent Environments

Author : M. Schneider
Publisher : IOS Press
ISBN 13 : 1607504642
Total Pages : 356 pages
Book Rating : 4.6/5 (75 download)

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Book Synopsis Workshops Proceedings of the 5th International Conference on Intelligent Environments by : M. Schneider

Download or read book Workshops Proceedings of the 5th International Conference on Intelligent Environments written by M. Schneider and published by IOS Press. This book was released on 2009-10-02 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in the engineering of sensing and acting capabilities distributed in wide range of specialized devices is providing at last an opportunity for the fundamental advances that computer science achieved in the past few decades to make an impact in our daily lives. This technical confluence is matched by a unique historical context where users are better informed (more aware of the benefits that technology can provide) and production of more complex systems is becoming more affordable. Sensors/actuators deployed in an environment (in this context it can be any physical space like a house, office, classroom, car, street, etc.) facilitate a link between an automated decision-making system connected to that technologically enriched space. This computing empowered environment enables the provision of an intelligent environment, i.e., "a digital environment that proactively, but sensibly, supports people in their daily lives". This is an active area of research which is attracting an increasing number of professionals (in academia and industry) worldwide. The prestigious 5th International Conference on Intelligent Environments (IE'09) is focused on the development of advanced intelligent environments and stimulates the discussion on several specific topics which are crucial to the future of the area. As part of that five workshops were supported as part of IE'09. This volume is the combined proceedings of those five workshops: Workshop on Digital Object Memories (DOMe'09), Workshop on RFID Technology: concepts, practices & solutions (RFID'09), Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI'09), Workshop on Ethical Design of Ambient Intelligence (EDAmI'09), Workshop on Smart Offices and Other Workplaces (SOOW'09).

Engineering Applications of Neural Networks

Author : John Macintyre
Publisher : Springer
ISBN 13 : 3030202577
Total Pages : 554 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Engineering Applications of Neural Networks by : John Macintyre

Download or read book Engineering Applications of Neural Networks written by John Macintyre and published by Springer. This book was released on 2019-05-14 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN 2019, held in Xersonisos, Crete, Greece, in May 2019. The 35 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on AI in energy management - industrial applications; biomedical - bioinformatics modeling; classification - learning; deep learning; deep learning - convolutional ANN; fuzzy - vulnerability - navigation modeling; machine learning modeling - optimization; ML - DL financial modeling; security - anomaly detection; 1st PEINT workshop.

Proceedings of the Second Workshop on Neural Networks

Author : Society for Computer Simulation
Publisher :
ISBN 13 :
Total Pages : 836 pages
Book Rating : 4.:/5 (318 download)

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Book Synopsis Proceedings of the Second Workshop on Neural Networks by : Society for Computer Simulation

Download or read book Proceedings of the Second Workshop on Neural Networks written by Society for Computer Simulation and published by . This book was released on 1991 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Deep Learning and Data Labeling for Medical Applications

Author : Gustavo Carneiro
Publisher : Springer
ISBN 13 : 3319469762
Total Pages : 289 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Deep Learning and Data Labeling for Medical Applications by : Gustavo Carneiro

Download or read book Deep Learning and Data Labeling for Medical Applications written by Gustavo Carneiro and published by Springer. This book was released on 2016-10-07 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.

Neural Networks Applications

Author : Patrick K. Simpson
Publisher : Institute of Electrical & Electronics Engineers(IEEE)
ISBN 13 :
Total Pages : 998 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Neural Networks Applications by : Patrick K. Simpson

Download or read book Neural Networks Applications written by Patrick K. Simpson and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1996 with total page 998 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume builds on and continues the excellent coverage of the subject established in the first volume with a special focus on cutting-edge applications. This book provides practicing engineers with a snapshot of the latest applications, supported by the most recent developments in neural networks theory and technology. You'll find state-of-the-art coverage of applications in: control, power systems, medical systems, information processing, signal processing manufacturing, production and inspection, vehicular technology, and more!

Adversarial Machine Learning

Author : Yevgeniy Tu
Publisher : Springer Nature
ISBN 13 : 3031015800
Total Pages : 152 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Adversarial Machine Learning by : Yevgeniy Tu

Download or read book Adversarial Machine Learning written by Yevgeniy Tu and published by Springer Nature. This book was released on 2022-05-31 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing abundance of large high-quality datasets, combined with significant technical advances over the last several decades have made machine learning into a major tool employed across a broad array of tasks including vision, language, finance, and security. However, success has been accompanied with important new challenges: many applications of machine learning are adversarial in nature. Some are adversarial because they are safety critical, such as autonomous driving. An adversary in these applications can be a malicious party aimed at causing congestion or accidents, or may even model unusual situations that expose vulnerabilities in the prediction engine. Other applications are adversarial because their task and/or the data they use are. For example, an important class of problems in security involves detection, such as malware, spam, and intrusion detection. The use of machine learning for detecting malicious entities creates an incentive among adversaries to evade detection by changing their behavior or the content of malicius objects they develop. The field of adversarial machine learning has emerged to study vulnerabilities of machine learning approaches in adversarial settings and to develop techniques to make learning robust to adversarial manipulation. This book provides a technical overview of this field. After reviewing machine learning concepts and approaches, as well as common use cases of these in adversarial settings, we present a general categorization of attacks on machine learning. We then address two major categories of attacks and associated defenses: decision-time attacks, in which an adversary changes the nature of instances seen by a learned model at the time of prediction in order to cause errors, and poisoning or training time attacks, in which the actual training dataset is maliciously modified. In our final chapter devoted to technical content, we discuss recent techniques for attacks on deep learning, as well as approaches for improving robustness of deep neural networks. We conclude with a discussion of several important issues in the area of adversarial learning that in our view warrant further research. Given the increasing interest in the area of adversarial machine learning, we hope this book provides readers with the tools necessary to successfully engage in research and practice of machine learning in adversarial settings.

Discovery

Author : United States Air Force Academy
Publisher :
ISBN 13 :
Total Pages : 278 pages
Book Rating : 4.:/5 (3 download)

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Book Synopsis Discovery by : United States Air Force Academy

Download or read book Discovery written by United States Air Force Academy and published by . This book was released on 1995 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Deep Learning with Keras Workshop

Author : Matthew Moocarme
Publisher : Packt Publishing Ltd
ISBN 13 : 1800564759
Total Pages : 495 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis The Deep Learning with Keras Workshop by : Matthew Moocarme

Download or read book The Deep Learning with Keras Workshop written by Matthew Moocarme and published by Packt Publishing Ltd. This book was released on 2020-07-29 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how to leverage Keras, the powerful and easy-to-use open source Python library for developing and evaluating deep learning models Key FeaturesGet to grips with various model evaluation metrics, including sensitivity, specificity, and AUC scoresExplore advanced concepts such as sequential memory and sequential modelingReinforce your skills with real-world development, screencasts, and knowledge checksBook Description New experiences can be intimidating, but not this one! This beginner's guide to deep learning is here to help you explore deep learning from scratch with Keras, and be on your way to training your first ever neural networks. What sets Keras apart from other deep learning frameworks is its simplicity. With over two hundred thousand users, Keras has a stronger adoption in industry and the research community than any other deep learning framework. The Deep Learning with Keras Workshop starts by introducing you to the fundamental concepts of machine learning using the scikit-learn package. After learning how to perform the linear transformations that are necessary for building neural networks, you'll build your first neural network with the Keras library. As you advance, you'll learn how to build multi-layer neural networks and recognize when your model is underfitting or overfitting to the training data. With the help of practical exercises, you'll learn to use cross-validation techniques to evaluate your models and then choose the optimal hyperparameters to fine-tune their performance. Finally, you'll explore recurrent neural networks and learn how to train them to predict values in sequential data. By the end of this book, you'll have developed the skills you need to confidently train your own neural network models. What you will learnGain insights into the fundamentals of neural networksUnderstand the limitations of machine learning and how it differs from deep learningBuild image classifiers with convolutional neural networksEvaluate, tweak, and improve your models with techniques such as cross-validationCreate prediction models to detect data patterns and make predictionsImprove model accuracy with L1, L2, and dropout regularizationWho this book is for If you know the basics of data science and machine learning and want to get started with advanced machine learning technologies like artificial neural networks and deep learning, then this is the book for you. To grasp the concepts explained in this deep learning book more effectively, prior experience in Python programming and some familiarity with statistics and logistic regression are a must.

Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques

Author : Olivas, Emilio Soria
Publisher : IGI Global
ISBN 13 : 1605667676
Total Pages : 734 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques by : Olivas, Emilio Soria

Download or read book Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques written by Olivas, Emilio Soria and published by IGI Global. This book was released on 2009-08-31 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.

Optimization for Machine Learning

Author : Suvrit Sra
Publisher : MIT Press
ISBN 13 : 026201646X
Total Pages : 509 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Optimization for Machine Learning by : Suvrit Sra

Download or read book Optimization for Machine Learning written by Suvrit Sra and published by MIT Press. This book was released on 2012 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.

Computational Electromagnetics—Retrospective and Outlook

Author : Iftikhar Ahmed
Publisher : Springer
ISBN 13 : 9812870954
Total Pages : 328 pages
Book Rating : 4.8/5 (128 download)

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Book Synopsis Computational Electromagnetics—Retrospective and Outlook by : Iftikhar Ahmed

Download or read book Computational Electromagnetics—Retrospective and Outlook written by Iftikhar Ahmed and published by Springer. This book was released on 2014-08-27 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book will cover the past, present and future developments of field theory and computational electromagnetics. The first two chapters will give an overview of the historical developments and the present the state-of-the-art in computational electromagnetics. These two chapters will set the stage for discussing recent progress, new developments, challenges, trends and major directions in computational electromagnetics with three main emphases: a. Modeling of ever larger structures with multi-scale dimensions and multi-level descriptions (behavioral, circuit, network and field levels) and transient behaviours b. Inclusions of physical effects other than electromagnetic: quantum effects, thermal effects, mechanical effects and nano scale features c. New developments in available computer hardware, programming paradigms (MPI, Open MP, CUDA and Open CL) and the associated new modeling approaches These are the current emerging topics in the area of computational electromagnetics and may provide readers a comprehensive overview of future trends and directions in the area. The book is written for students, research scientists, professors, design engineers and consultants who engaged in the fields of design, analysis and research of the emerging technologies related to computational electromagnetics, RF/microwave, optimization, new numerical methods, as well as accelerator simulator, dispersive materials, nano-antennas, nano-waveguide, nano-electronics, terahertz applications, bio-medical and material sciences. The book may also be used for those involved in commercializing electromagnetic and related emerging technologies, sensors and the semiconductor industry. The book can be used as a reference book for graduates and post graduates. It can also be used as a text book for workshops and continuing education for researchers and design engineers.