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Multimodal Machine Learning

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Multimodal Scene Understanding

Multimodal Scene Understanding Book
Author : Michael Yang,Bodo Rosenhahn,Vittorio Murino
Publisher : Academic Press
Release : 2019-07-16
ISBN : 0128173599
Language : En, Es, Fr & De

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Book Description :

Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. Contains state-of-the-art developments on multi-modal computing Shines a focus on algorithms and applications Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning

Multimodal Learning for Clinical Decision Support and Clinical Image Based Procedures

Multimodal Learning for Clinical Decision Support and Clinical Image Based Procedures Book
Author : Tanveer Syeda-Mahmood,Klaus Drechsler,Hayit Greenspan,Anant Madabhushi,Alexandros Karargyris,Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Marius Erdt
Publisher : Springer Nature
Release : 2020-10-03
ISBN : 3030609464
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed joint proceedings of the 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. The 4 full papers presented at ML-CDS 2020 and the 9 full papers presented at CLIP 2020 were carefully reviewed and selected from numerous submissions to ML-CDS and 10 submissions to CLIP. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The CLIP workshops provides a forum for work centered on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.

Multimodal Machine Learning

Multimodal Machine Learning Book
Author : Santosh Kumar,Sanjay Kumar Singh
Publisher : Academic Press
Release : 2021-05-15
ISBN : 9780128237373
Language : En, Es, Fr & De

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Book Description :

Multimodal Machine Learning: Techniques and Applications explains recent advances in multimodal machine learning, providing a coherent set of fundamentals for designing efficient multimodal learning algorithms for different applications. The book addresses the main challenges in multimodal machine learning based computing paradigms, including multimodal representation learning, translation and mapping, modality alignment, multimodal fusion and co-learning. The book also explores the important texture feature descriptors based on recognition and transform techniques. It is ideal for senior undergraduates, graduate students, and researchers in data science, engineering, computer science and statistics. Presents new representation, classification and identification algorithms for data prediction and analysis on feature characteristics Discusses recent and future advancements in diversified fields of computer vision , pattern recognition, generative adversarial network-based learning, video analytics and data science Provides an overview of future research challenges and directions

Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support

Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support Book
Author : Kenji Suzuki,Mauricio Reyes,Tanveer Syeda-Mahmood,Ender Konukoglu,Ben Glocker,Roland Wiest,Yaniv Gur,Hayit Greenspan,Anant Madabhushi
Publisher : Springer Nature
Release : 2019-10-24
ISBN : 3030338509
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS 2019 were carefully reviewed and selected from 10 submissions to iMIMIC and numerous submissions to ML-CDS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support Book
Author : M. Jorge Cardoso,Tal Arbel,Gustavo Carneiro,Tanveer Syeda-Mahmood,João Manuel R.S. Tavares,Mehdi Moradi,Andrew Bradley,Hayit Greenspan,João Paulo Papa,Anant Madabhushi,Jacinto C. Nascimento,Jaime S. Cardoso,Vasileios Belagiannis,Zhi Lu
Publisher : Springer
Release : 2017-09-07
ISBN : 3319675583
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

Deep Neural Networks for Multimodal Imaging and Biomedical Applications

Deep Neural Networks for Multimodal Imaging and Biomedical Applications Book
Author : Annamalai Suresh,R. Udendran,S. Vimal
Publisher : Unknown
Release : 2020
ISBN : 9781799835912
Language : En, Es, Fr & De

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Book Description :

"This book provides research exploring the theoretical and practical aspects of emerging data computing methods and imaging techniques within healthcare and biomedicine. The publication provides a complete set of information in a single module starting from developing deep neural networks to predicting disease by employing multi-modal imaging"--

Big Data in Multimodal Medical Imaging

Big Data in Multimodal Medical Imaging Book
Author : Ayman El-Baz,Jasjit S. Suri
Publisher : CRC Press
Release : 2019-11-06
ISBN : 1351380729
Language : En, Es, Fr & De

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Book Description :

There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems.

Multimodal Sentiment Analysis

Multimodal Sentiment Analysis Book
Author : Soujanya Poria,Amir Hussain,Erik Cambria
Publisher : Springer
Release : 2018-10-24
ISBN : 3319950207
Language : En, Es, Fr & De

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Book Description :

This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer. This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion. The inclusion of key visualization and case studies will enable readers to understand better these approaches. Aimed at the Natural Language Processing, Affective Computing and Artificial Intelligence audiences, this comprehensive volume will appeal to a wide readership and will help readers to understand key details on multimodal sentiment analysis.

Multimodal Analytics for Next Generation Big Data Technologies and Applications

Multimodal Analytics for Next Generation Big Data Technologies and Applications Book
Author : Kah Phooi Seng,Li-minn Ang,Alan Wee-Chung Liew,Junbin Gao
Publisher : Springer
Release : 2019-07-18
ISBN : 3319975986
Language : En, Es, Fr & De

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Book Description :

This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications. The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.

Challenges and Trends in Multimodal Fall Detection for Healthcare

Challenges and Trends in Multimodal Fall Detection for Healthcare Book
Author : Hiram Ponce,Lourdes Martínez-Villaseñor,Jorge Brieva,Ernesto Moya-Albor
Publisher : Springer Nature
Release : 2020-01-28
ISBN : 3030387488
Language : En, Es, Fr & De

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Book Description :

This book focuses on novel implementations of sensor technologies, artificial intelligence, machine learning, computer vision and statistics for automated, human fall recognition systems and related topics using data fusion. It includes theory and coding implementations to help readers quickly grasp the concepts and to highlight the applicability of this technology. For convenience, it is divided into two parts. The first part reviews the state of the art in human fall and activity recognition systems, while the second part describes a public dataset especially curated for multimodal fall detection. It also gathers contributions demonstrating the use of this dataset and showing examples. This book is useful for anyone who is interested in fall detection systems, as well as for those interested in solving challenging, signal recognition, vision and machine learning problems. Potential applications include health care, robotics, sports, human–machine interaction, among others.

Medical Image Computing and Computer Assisted Intervention MICCAI 2016

Medical Image Computing and Computer Assisted Intervention     MICCAI 2016 Book
Author : Sebastien Ourselin,Leo Joskowicz,Mert R. Sabuncu,Gozde Unal,William Wells
Publisher : Springer
Release : 2016-10-17
ISBN : 3319467239
Language : En, Es, Fr & De

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Book Description :

The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, held in Athens, Greece, in October 2016. Based on rigorous peer reviews, the program committee carefully selected 228 revised regular papers from 756 submissions for presentation in three volumes. The papers have been organized in the following topical sections: Part I: brain analysis, brain analysis - connectivity; brain analysis - cortical morphology; Alzheimer disease; surgical guidance and tracking; computer aided interventions; ultrasound image analysis; cancer image analysis; Part II: machine learning and feature selection; deep learning in medical imaging; applications of machine learning; segmentation; cell image analysis; Part III: registration and deformation estimation; shape modeling; cardiac and vascular image analysis; image reconstruction; and MR image analysis.

Multimodal Signal Processing

Multimodal Signal Processing Book
Author : Jean-Philippe Thiran,Ferran Marqués,Hervé Bourlard
Publisher : Academic Press
Release : 2009-11-11
ISBN : 9780080888699
Language : En, Es, Fr & De

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Book Description :

Multimodal signal processing is an important research and development field that processes signals and combines information from a variety of modalities – speech, vision, language, text – which significantly enhance the understanding, modelling, and performance of human-computer interaction devices or systems enhancing human-human communication. The overarching theme of this book is the application of signal processing and statistical machine learning techniques to problems arising in this multi-disciplinary field. It describes the capabilities and limitations of current technologies, and discusses the technical challenges that must be overcome to develop efficient and user-friendly multimodal interactive systems. With contributions from the leading experts in the field, the present book should serve as a reference in multimodal signal processing for signal processing researchers, graduate students, R&D engineers, and computer engineers who are interested in this emerging field. Presents state-of-art methods for multimodal signal processing, analysis, and modeling Contains numerous examples of systems with different modalities combined Describes advanced applications in multimodal Human-Computer Interaction (HCI) as well as in computer-based analysis and modelling of multimodal human-human communication scenes.

The Handbook of Multimodal Multisensor Interfaces Volume 2

The Handbook of Multimodal Multisensor Interfaces  Volume 2 Book
Author : Sharon Oviatt,Björn Schuller,Philip Cohen,Daniel Sonntag,Gerasimos Potamianos,Antonio Krüger
Publisher : Morgan & Claypool
Release : 2018-10-08
ISBN : 1970001690
Language : En, Es, Fr & De

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Book Description :

The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.

Remote Sensing Imagery

Remote Sensing Imagery Book
Author : Florence Tupin,Jordi Inglada,Jean-Marie Nicolas
Publisher : John Wiley & Sons
Release : 2014-02-19
ISBN : 1118898923
Language : En, Es, Fr & De

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Book Description :

Dedicated to remote sensing images, from their acquisition to theiruse in various applications, this book covers the global lifecycleof images, including sensors and acquisition systems, applicationssuch as movement monitoring or data assimilation, and image anddata processing. It is organized in three main parts. The first part presentstechnological information about remote sensing (choice of satelliteorbit and sensors) and elements of physics related to sensing(optics and microwave propagation). The second part presents imageprocessing algorithms and their specificities for radar or optical,multi and hyper-spectral images. The final part is devoted toapplications: change detection and analysis of time series,elevation measurement, displacement measurement and dataassimilation. Offering a comprehensive survey of the domain of remote sensingimagery with a multi-disciplinary approach, this book is suitablefor graduate students and engineers, with backgrounds either incomputer science and applied math (signal and image processing) orgeo-physics. About the Authors Florence Tupin is Professor at Telecom ParisTech, France. Herresearch interests include remote sensing imagery, image analysisand interpretation, three-dimensional reconstruction, and syntheticaperture radar, especially for urban remote sensingapplications. Jordi Inglada works at the Centre National d’ÉtudesSpatiales (French Space Agency), Toulouse, France, in the field ofremote sensing image processing at the CESBIO laboratory. He is incharge of the development of image processing algorithms for theoperational exploitation of Earth observation images, mainly in thefield of multi-temporal image analysis for land use and coverchange. Jean-Marie Nicolas is Professor at Telecom ParisTech in the Signaland Imaging department. His research interests include the modelingand processing of synthetic aperture radar images.

The Handbook of Multimodal Multisensor Interfaces Volume 1

The Handbook of Multimodal Multisensor Interfaces  Volume 1 Book
Author : Sharon Oviatt,Björn Schuller,Philip Cohen,Daniel Sonntag,Gerasimos Potamianos
Publisher : Morgan & Claypool
Release : 2017-06-01
ISBN : 1970001666
Language : En, Es, Fr & De

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Book Description :

The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces— user input involving new media (speech, multi-touch, gestures, writing) embedded in multimodal-multisensor interfaces. These interfaces support smart phones, wearables, in-vehicle and robotic applications, and many other areas that are now highly competitive commercially. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This first volume of the handbook presents relevant theory and neuroscience foundations for guiding the development of high-performance systems. Additional chapters discuss approaches to user modeling and interface designs that support user choice, that synergistically combine modalities with sensors, and that blend multimodal input and output. This volume also highlights an in-depth look at the most common multimodal-multisensor combinations—for example, touch and pen input, haptic and non-speech audio output, and speech-centric systems that co-process either gestures, pen input, gaze, or visible lip movements. A common theme throughout these chapters is supporting mobility and individual differences among users. These handbook chapters provide walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this emerging field. In the final section of this volume, experts exchange views on a timely and controversial challenge topic, and how they believe multimodal-multisensor interfaces should be designed in the future to most effectively advance human performance.

Machine Learning Systems for Multimodal Affect Recognition

Machine Learning Systems for Multimodal Affect Recognition Book
Author : Markus Kächele
Publisher : Springer Nature
Release : 2019-11-19
ISBN : 3658286741
Language : En, Es, Fr & De

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Book Description :

Markus Kächele offers a detailed view on the different steps in the affective computing pipeline, ranging from corpus design and recording over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers. He focuses on multimodal recognition of discrete and continuous emotional and medical states. As such, specifically the peculiarities that arise during annotation and processing of continuous signals are highlighted. Furthermore, methods are presented that allow personalization of datasets and adaptation of classifiers to new situations and persons.

Multimodal Agents for Ageing and Multicultural Societies

Multimodal Agents for Ageing and Multicultural Societies Book
Author : Juliana Miehle,Wolfgang Minker,Elisabeth André,Koichiro Yoshino
Publisher : Springer Nature
Release : 2021-10-09
ISBN : 9811634769
Language : En, Es, Fr & De

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Book Description :

This book aims to explore and discuss theories and technologies for the development of socially competent and culture-aware embodied conversational agents for elderly care. To tackle the challenges in ageing societies, this book was written by experts who have a background in assistive technologies for elderly care, culture-aware computing, multimodal dialogue, social robotics and synthetic agents. Chapter 1 presents a vision of an intelligent agent to illustrate the current challenges for the design and development of adaptive systems. Chapter 2 examines how notions of trust and empathy may be applied to human–robot interaction and how it can be used to create the next generation of emphatic agents, which address some of the pressing issues in multicultural ageing societies. Chapter 3 discusses multimodal machine learning as an approach to enable more effective and robust modelling technologies and to develop socially competent and culture-aware embodied conversational agents for elderly care. Chapter 4 explores the challenges associated with real-world field tests and deployments. Chapter 5 gives a short introduction to socio-cognitive language processing that describes the idea of coping with everyday language, irony, sarcasm, humor, paralinguistic information such as the physical and mental state and traits of the dialogue partner, and social aspects. This book grew out of the Shonan Meeting seminar entitled “Multimodal Agents for Ageing and Multicultural Societies” held in 2018 in Japan. Researchers and practitioners will be helped to understand the emerging field and the identification of promising approaches from a variety of disciplines such as human–computer interaction, artificial intelligence, modelling, and learning.

Deep Learning

Deep Learning Book
Author : Li Deng,Dong Yu
Publisher : Unknown
Release : 2014
ISBN : 9781601988140
Language : En, Es, Fr & De

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Book Description :

Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks

Multimodal Behavior Analysis in the Wild

Multimodal Behavior Analysis in the Wild Book
Author : Xavier Alameda-Pineda,Elisa Ricci,Nicu Sebe
Publisher : Academic Press
Release : 2018-11-13
ISBN : 0128146028
Language : En, Es, Fr & De

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Book Description :

Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data

Multimodal Biometric Systems

Multimodal Biometric Systems Book
Author : Rashmi Gupta,Manju Khari
Publisher : CRC Press
Release : 2021-09-26
ISBN : 1000453782
Language : En, Es, Fr & De

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Book Description :

Many governments around the world are calling for the use of biometric systems to provide crucial societal functions, consequently making it an urgent area for action. The current performance of some biometric systems in terms of their error rates, robustness, and system security may prove to be inadequate for large-scale applications to process millions of users at a high rate of throughput. This book focuses on fusion in biometric systems. It discusses the present level, the limitations, and proposed methods to improve performance. It describes the fundamental concepts, current research, and security-related issues. The book will present a computational perspective, identify challenges, and cover new problem-solving strategies, offering solved problems and case studies to help with reader comprehension and deep understanding. This book is written for researchers, practitioners, both undergraduate and post-graduate students, and those working in various engineering fields such as Systems Engineering, Computer Science, Information Technology, Electronics, and Communications.