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Author : Nathan Gaw
Publisher : Springer Nature
Page : 388 pages
File Size : 48,5 Mb
Release : 2024-06-02
Category : Electronic
ISBN : 9783031530920
Author : Kah Phooi Seng,Li-minn Ang,Alan Wee-Chung Liew,Junbin Gao
Publisher : Springer
Page : 391 pages
File Size : 45,7 Mb
Release : 2019-07-18
Category : Computers
ISBN : 9783319975986
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.
Author : Dewan Masud Karim
Publisher : CRC Press
Page : 410 pages
File Size : 51,5 Mb
Release : 2023-12-01
Category : Computers
ISBN : 9781003822820
In the face of resource depletion, environmental changes, lifestyle changes, demographic and digital adaptation, old ideologies of city building and expensive and complex automobility solutions are in freefall. These changes are creating severe friction between the old and new paradigms. This book provides new perspectives through the process of ideological disassociation and concepts of human mobility code. The basic premise of the book, human mobility is an essential component of our creativity that comes from our unconscious desire to become a part of a community. Several new concepts in the book starts with the hallmark of new discovery of human mobility code and its implications of urban mobility boundary systems to stay within safe planetary zone. A new discovery of human mobility code from comprehensive research finding prove that each individual develops a unique mobility footprint and become our mobility identity. Beyond individual hallmarks, human develops collective mobility codes through interaction with the third space on which entire mobility systems lie and are created by the fundamentals of city planning and the design process. Readers are introduced to an innovative mobility planning process and reinvention of multimodal mobility approaches based on new mobility code while formulating new concepts, practical solutions and implementation techniques, tools, policies, and processes to reinforce low-carbon mobility options while addressing social equity, environmental, and health benefits. Finally, the book arms us with knowledge to prevent the disaster of full technological enlightenment against our natural human mobility code.
Author : Yuhui Zheng,Zexuan Ji,Heye Zhang,Jonathan Wu
Publisher : Frontiers Media SA
Page : 108 pages
File Size : 46,9 Mb
Release : 2021-09-23
Category : Science
ISBN : 9782889713493
Author : Tania Stathaki
Publisher : Elsevier
Page : 520 pages
File Size : 44,5 Mb
Release : 2011-08-29
Category : Computers
ISBN : 0080558526
The growth in the use of sensor technology has led to the demand for image fusion: signal processing techniques that can combine information received from different sensors into a single composite image in an efficient and reliable manner. This book brings together classical and modern algorithms and design architectures, demonstrating through applications how these can be implemented. Image Fusion: Algorithms and Applications provides a representative collection of the recent advances in research and development in the field of image fusion, demonstrating both spatial domain and transform domain fusion methods including Bayesian methods, statistical approaches, ICA and wavelet domain techniques. It also includes valuable material on image mosaics, remote sensing applications and performance evaluation. This book will be an invaluable resource to R&D engineers, academic researchers and system developers requiring the most up-to-date and complete information on image fusion algorithms, design architectures and applications. Combines theory and practice to create a unique point of reference Contains contributions from leading experts in this rapidly-developing field Demonstrates potential uses in military, medical and civilian areas
Author : Baby Maruthi, Puvvadi,Prasad, Smrity,Tyagi, Amit Kumar
Publisher : IGI Global
Page : 473 pages
File Size : 40,9 Mb
Release : 2023-12-18
Category : Computers
ISBN : 9781668485330
Machine learning is able to solve real-time problems. It has several algorithms such as classification, clustering, and more. To learn these essential algorithms, we require tools like Scikit and TensorFlow. Machine Learning Algorithms Using Scikit and TensorFlow Environments assists researchers in learning and implementing these critical algorithms. Covering key topics such as classification, artificial neural networks, prediction, random forest, and regression analysis, this premier reference source is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
Author : Anonim
Publisher : Unknown
Page : 970 pages
File Size : 53,5 Mb
Release : 1975
Category : Aeronautics
ISBN : UIUC:30112057085133
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Author : Arturo Román Messina
Publisher : CRC Press
Page : 267 pages
File Size : 47,8 Mb
Release : 2020-05-05
Category : Mathematics
ISBN : 9781000065893
Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining techniques for power system monitoring with focus on use of synchronized phasor networks. Relevant statistical data mining techniques are given, and efficient methods to cluster and visualize data collected from multiple sensors are discussed. Both linear and nonlinear data-driven mining and fusion techniques are reviewed, with emphasis on the analysis and visualization of massive distributed data sets. Challenges involved in realistic monitoring, visualization, and analysis of observation data from actual events are also emphasized, supported by examples of relevant applications. Features Focuses on systematic illustration of data mining and fusion in power systems Covers issues of standards used in the power industry for data mining and data analytics Applications to a wide range of power networks are provided including distribution and transmission networks Provides holistic approach to the problem of data mining and data fusion using cutting-edge methodologies and technologies Includes applications to massive spatiotemporal data from simulations and actual events
Author : Annamalai Suresh,R. Udendran,S. Vimal
Publisher : Medical Information Science Reference
Page : 294 pages
File Size : 53,6 Mb
Release : 2020
Category : Computers
ISBN : 1799835936
The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells. Implementing these biomedical technologies remains a challenge for hospitals worldwide, creating a need for research on the specific applications of these computational techniques. Deep Neural Networks for Multimodal Imaging and Biomedical Applications 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. Featuring coverage on a broad range of topics such as prediction models, edge computing, and quantitative measurements, this book is ideally designed for researchers, academicians, physicians, IT consultants, medical software developers, practitioners, policymakers, scholars, and students seeking current research on biomedical advancements and developing computational methods in healthcare.
Author : Paolo Barsocchi,Naga Srinivasu Parvathaneni,Amik Garg,Akash Kumar Bhoi,Filippo Palumbo
Publisher : Springer Nature
Page : 322 pages
File Size : 45,8 Mb
Release : 2023-10-03
Category : Technology & Engineering
ISBN : 9783031382819
This book experiences the future of patient-centered healthcare and dives into the latest advancements and transformative technologies that are revolutionizing the well-being of individuals around the globe. The readers can join authors on an engaging journey as the authors explore the captivating realm of ambient assisted living and unlock its immense potential for improving healthcare outcomes. This book goes beyond mere exploration; it invites readers to embark on a voyage of discovery as authors unveil the outcomes of groundbreaking research ideas. With a diverse range of applications, from deep learning in healthcare to cutting-edge models, the authors offer a comprehensive view of the opportunities and challenges that lie ahead. Whether you're a healthcare professional, an academic seeking the latest insights, or a researcher delving into the realms of ambient assistive technology, biomedical engineering, or computational intelligence, this book is an invaluable resource. Additionally, postgraduate students pursuing data engineering systems find it to be an essential guide. Each chapter stands independently, providing a comprehensive overview of problem formulation and its tangible outcomes. The readers can immerse themselves in the world of patient-centered healthcare today and become part of the forefront of innovation.
Author : Khalid Saeed
Publisher : CRC Press
Page : 144 pages
File Size : 54,8 Mb
Release : 2016-10-14
Category : Computers
ISBN : 9781315349312
Automatic biometrics recognition techniques are increasingly important in corporate and public security systems and have increased in methods due to rapid field development. This book discusses classic behavioral biometrics as well as collects the latest advances in techniques, theoretical approaches, and dynamic applications. This future-looking book is an important reference tool for researchers, practitioners, academicians, and technologists. While there are existing books that focus on physiological biometrics or algorithmic approaches deployed in biometrics, this book addresses a gap in the existing literature for a text that is solely dedicated to the topic of behavioral biometrics.
Author : Eric Moreau,Tülay Adali
Publisher : John Wiley & Sons
Page : 112 pages
File Size : 54,8 Mb
Release : 2013-10-07
Category : Technology & Engineering
ISBN : 9781848214590
Blind identification consists of estimating a multi-dimensional system only through the use of its output, and source separation, the blind estimation of the inverse of the system. Estimation is generally carried out using different statistics of the output. The authors of this book consider the blind identification and source separation problem in the complex-domain, where the available statistical properties are richer and include non-circularity of the sources – underlying components. They define identifiability conditions and present state-of-the-art algorithms that are based on algebraic methods as well as iterative algorithms based on maximum likelihood theory. Contents 1. Mathematical Preliminaries. 2. Estimation by Joint Diagonalization. 3. Maximum Likelihood ICA. About the Authors Eric Moreau is Professor of Electrical Engineering at the University of Toulon, France. His research interests concern statistical signal processing, high order statistics and matrix/tensor decompositions with applications to data analysis, telecommunications and radar. Tülay Adali is Professor of Electrical Engineering and Director of the Machine Learning for Signal Processing Laboratory at the University of Maryland, Baltimore County, USA. Her research interests concern statistical and adaptive signal processing, with an emphasis on nonlinear and complex-valued signal processing, and applications in biomedical data analysis and communications. Blind identification consists of estimating a multidimensional system through the use of only its output. Source separation is concerned with the blind estimation of the inverse of the system. The estimation is generally performed by using different statistics of the outputs. The authors consider the blind estimation of a multiple input/multiple output (MIMO) system that mixes a number of underlying signals of interest called sources. They also consider the case of direct estimation of the inverse system for the purpose of source separation. They then describe the estimation theory associated with the identifiability conditions and dedicated algebraic algorithms. The algorithms depend critically on (statistical and/or time frequency) properties of complex sources that will be precisely described.
Author : Andrzej Cichocki,Rafal Zdunek,Anh Huy Phan,Shun-ichi Amari
Publisher : John Wiley & Sons
Page : 500 pages
File Size : 46,5 Mb
Release : 2009-07-10
Category : Science
ISBN : 0470747285
This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF’s various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and data analysis, having garnered interest due to their capability to provide new insights and relevant information about the complex latent relationships in experimental data sets. It is suggested that NMF can provide meaningful components with physical interpretations; for example, in bioinformatics, NMF and its extensions have been successfully applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining. As such, the authors focus on the algorithms that are most useful in practice, looking at the fastest, most robust, and suitable for large-scale models. Key features: Acts as a single source reference guide to NMF, collating information that is widely dispersed in current literature, including the authors’ own recently developed techniques in the subject area. Uses generalized cost functions such as Bregman, Alpha and Beta divergences, to present practical implementations of several types of robust algorithms, in particular Multiplicative, Alternating Least Squares, Projected Gradient and Quasi Newton algorithms. Provides a comparative analysis of the different methods in order to identify approximation error and complexity. Includes pseudo codes and optimized MATLAB source codes for almost all algorithms presented in the book. The increasing interest in nonnegative matrix and tensor factorizations, as well as decompositions and sparse representation of data, will ensure that this book is essential reading for engineers, scientists, researchers, industry practitioners and graduate students across signal and image processing; neuroscience; data mining and data analysis; computer science; bioinformatics; speech processing; biomedical engineering; and multimedia.
Author : Amit Kumar,Sabrina Senatore,Vinit Kumar Gunjan
Publisher : Springer Nature
Page : 875 pages
File Size : 50,6 Mb
Release : 2023-02-06
Category : Technology & Engineering
ISBN : 9789811959363
This book gathers selected high-impact articles from the 3rd International Conference on Data Science, Machine Learning & Applications 2021. It highlights the latest developments in the areas of artificial intelligence, machine learning, soft computing, human–computer interaction and various data science and machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.
Author : Peggy Cellier,Kurt Driessens
Publisher : Springer Nature
Page : 688 pages
File Size : 55,5 Mb
Release : 2020-03-27
Category : Computers
ISBN : 9783030438234
This two-volume set constitutes the refereed proceedings of the workshops which complemented the 19th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in Würzburg, Germany, in September 2019. The 70 full papers and 46 short papers presented in the two-volume set were carefully reviewed and selected from 200 submissions. The two volumes (CCIS 1167 and CCIS 1168) present the papers that have been accepted for the following workshops: Workshop on Automating Data Science, ADS 2019; Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence and eXplainable Knowledge Discovery in Data Mining, AIMLAI-XKDD 2019; Workshop on Decentralized Machine Learning at the Edge, DMLE 2019; Workshop on Advances in Managing and Mining Large Evolving Graphs, LEG 2019; Workshop on Data and Machine Learning Advances with Multiple Views; Workshop on New Trends in Representation Learning with Knowledge Graphs; Workshop on Data Science for Social Good, SoGood 2019; Workshop on Knowledge Discovery and User Modelling for Smart Cities, UMCIT 2019; Workshop on Data Integration and Applications Workshop, DINA 2019; Workshop on Machine Learning for Cybersecurity, MLCS 2019; Workshop on Sports Analytics: Machine Learning and Data Mining for Sports Analytics, MLSA 2019; Workshop on Categorising Different Types of Online Harassment Languages in Social Media; Workshop on IoT Stream for Data Driven Predictive Maintenance, IoTStream 2019; Workshop on Machine Learning and Music, MML 2019; Workshop on Large-Scale Biomedical Semantic Indexing and Question Answering, BioASQ 2019. The chapter "Supervised Human-guided Data Exploration" is published open access under a Creative Commons Attribution 4.0 International license (CC BY).