Litgu.ru - Литературный Гуру

Название: Теория и проектирование быстрых перестраиваемых преобразований и слабосвязанных нейронных сетей
Автор: Дорогов А.Ю.
Издательство: СПб.: Пoлитехника
Год: 2014
Формат: pdf
Страниц: 327
Размер: 19 mb
Язык: Русский

В монографии дается современное изложение теории проектирования алгоритмов быстрых преобразований и модульных нейронных сетей. С системных позиций рассматриваются быстрые преобразования и многослойные нейронные сети с прореженным набором связей и модульной организацией. Предложены алгоритмы структурного проектирования и обучения перестраиваемых быстрых преобразований и нейронных сетей.

Название: Computational Intelligence Aided Systems for Healthcare Domain
Автор: Akshansh Gupta, Hanuman Verma, Mukesh Prasad
Издательство: CRC Press
Год: 2023
Страниц: 437
Язык: английский
Формат: pdf (true)
Размер: 79.4 MB

This book covers recent advances in Artificial Intelligence (AI), smart computing, and their applications in augmenting medical and health care systems. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical. Machine Learning is a learning process by the computing device; that is the study of computer algorithms that improve automatically through experience and by using input data. Thus, the machine learning algorithms are processes that can learn from the data. This is accomplished with the minimum extent of human intervention without explicit programming like in abstraction form. The learning process in Machine Learning is improved based on the experiences of the machines throughout the execution process. It builds a model or map based on training data that can be used to make predictions or decisions.

Название: Introductory Applied Statistics: With Resampling Methods & R
Автор: Bruce Blaine
Издательство: Springer
Год: 2023
Страниц: 197
Язык: английский
Формат: pdf (true), epub
Размер: 27.8 MB

Includes data analytic examples in R. This book offers an introduction to applied statistics through data analysis, integrating statistical computing methods. It covers robust and non-robust descriptive statistics used in each of four bivariate statistical models that are commonly used in research: ANOVA, proportions, regression, and logistic. The text teaches statistical inference principles using resampling methods (such as randomization and bootstrapping), covering methods for hypothesis testing and parameter estimation. These methods are applied to each statistical model introduced in preceding chapters. Data analytic examples are used to teach statistical concepts throughout, and students are introduced to the R packages and functions required for basic data analysis in each of the four models. The text also includes introductory guidance to the fundamentals of data wrangling, as well as examples of write-ups so that students can learn how to communicate findings. Each chapter includes problems for practice or assessment. Supplemental instructional videos are also available as an additional aid to instructors, or as a general resource to students.

Название: Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges
Автор: Ziheng Sun, Nicoleta Cristea, Pablo Rivas
Издательство: Elsevier
Год: 2023
Страниц: 430
Язык: английский
Формат: pdf (true)
Размер: 42.9 MB

Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges provides a comprehensive, step-by-step guide to AI workflows for solving problems in Earth Science. The book focuses on the most challenging problems in applying AI in Earth system sciences, such as training data preparation, model selection, hyperparameter tuning, model structure optimization, spatiotemporal generalization, transforming model results into products, and explaining trained models. In addition, it provides full-stack workflow tutorials to help walk readers through the whole process, regardless of previous AI experience. Artificial Intelligence (AI) technologies have been aggressively experimented with in Earth system sciences and attempted to solve these urgent problems and provide a solution for those ultimate challenges of humanity. Deep Learning has become one of the most popular research areas and could almost be seen in every branch of Earth sciences today. The idea behind Deep Learning is based on adding more hidden layers to the neural network, using a series of methods to control the model regularization and balance between overfitting and underfitting.

Название: Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods
Автор: Kemal Polat, Saban Ozturk
Издательство: Academic Press/Elsevier
Год: 2023
Страниц: 303
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Deep learning (DL), which has transformed several industries over the past ten years, has astounded practitioners with its amazing performance across nearly all application domains. The following fundamental ideas related to DL can be arranged in order of breadth to depth: (1) the brain-inspired artificial neural network (ANN) algorithm; (2) Machine Learning (ML) methods that allow machines to learn from examples without having to be explicitly programmed; and (3) Artificial Intelligence (AI), a theory that aims to artificially mimic the intelligent behavior of beings found in nature.

Название: Cybersecurity for eHealth: A Simplified Guide to Practical Cybersecurity for Non-technical Stakeholders & Practitioners
Автор: Emmanuel C. Ogu
Издательство: CRC Press
Год: 2022
Страниц: 135
Язык: английский
Формат: pdf (true), epub (true)
Размер: 14.5 MB

The modern realities of cybersecurity have uncovered the unpreparedness of many sectors and industries to deal with emerging threats. One of these sectors is the healthcare industry. The pervasiveness and proliferation of digital innovation, systems, and applications in global healthcare, especially powered by modern information and communications technologies, have created a threat domain wherein policy and regulation struggle to keep pace with development, standardization faces contextual challenges, and technical capacity is largely deficient. It is now urgent that healthcare professionals understand the most relevant concepts and fundamentals of global cybersecurity related to healthcare (particularly eHealth). Cybersecurity for eHealth: A Practical Guide for Non-Technical Healthcare Stakeholders & Practitioners combines a rigorous academic and practical professional approach in covering the essentials of cybersecurity.

Название: Deep Learning in Time Series Analysis
Автор: Arash Gharehbaghi
Издательство: CRC Press
Год: 2023
Страниц: 208
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Deep Learning is an important element of Artificial Intelligence, especially in applications such as image classification in which various architectures of neural network, e.g., convolutional neural networks, have yielded reliable results. This book introduces Deep Learning for time series analysis, particularly for cyclic time series. It elaborates on the methods employed for time series analysis at the deep level of their architectures. Cyclic time series usually have special traits that can be employed for better classification performance. These are addressed in the book. Processing cyclic time series is also covered herein. The book has been designed as a self-learning textbook for the readers with different backgrounds and understanding levels of Machine Learning, including students, engineers, researchers, and scientists of this domain. The numerous informative illustrations presented by the book will lead the readers to a deep level of understanding about the Deep Learning methods for time series analysis.

Название: Computer Vision and Image Analysis for Industry 4.0
Автор: Nazmul Siddique, Mohammad Shamsul Arefin, Atiqur Rahman Ahad
Издательство: CRC Press
Год: 2023
Страниц: 214
Язык: английский
Формат: pdf (true)
Размер: 28.8 MB

Computer vision and image analysis are indispensable components of every automated environment. Modern machine vision and image analysis techniques play key roles in automation and quality assurance. Working environments can be improved significantly if we integrate Computer Vision and image analysis techniques. The more advancement in innovation and research in Computer Vision and image processing, the greater the efficiency of machines as well as humans. A Deep Learning Approach in Detailed Fingerprint Identification: Fingerprints, as one of the most acceptable biometrics, has a significant use for security purposes. In today’s world, fingerprints are utilized in criminal investigations for identification purposes. Fingerprints can be used to identify a person’s gender, hand, finger, and other relevant aspects. The required time and effort in identifying an individual can be reduced by gender, hand, and finger classifications using fingerprints. In this chapter, a very simple model based on Convolutional Neural Networks (CNNs) is proposed to classify fingerprints by gender, hand, and finger. Convolutional Neural Network has achieved significant performance in image classification due to its ability for extraction of prominent features from complex images.

Название: Applied Intelligence for Industry 4.0
Автор: Nazmul Siddique, Mohammad Shamsul Arefin, M. Shamim Kaiser
Издательство: CRC Press
Год: 2023
Страниц: 279
Язык: английский
Формат: pdf (true)
Размер: 24.9 MB

We are all aware that Artificial Intelligence (AI) has brought a change in our lives, driven by a new form of interaction between man and machine. We are in the era of the fourth Industrial Revolution (IR) where AI plays vital roles in human development by enabling extraordinary technological advances making fundamental changes to the way we live, work and relate to one another. It is an opportunity to help everyone, including leaders, policymakers and people from all income groups and nations, to harness converging technologies in order to create an inclusive, human-centered future. Analyzing the IT Job Market and Classifying IT Jobs Using Machine Learning Algorithms: Machine Learning (ML) algorithms are used to classify analogous jobs. Convolutional Networks (CNNs) have been used to establish job classification systems based on job requirement text. Several ML approaches such as Gradient Boosting, Logistic Regression, Gaussian Naive Bayes, Support Vector Machine (SVM), Random Forest, and K-Nearest Neighbors (KNN) have been applied for classifying IT jobs.

Название: PowerShell: A Beginner's Guide to Windows PowerShell
Автор: Roger Wilson
Издательство: Ingram Publishing
Год: 2022
Страниц: 108
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Windows PowerShell is a scripting language and automation engine that is designed using object-oriented concepts with the .NET framework. It provides a Graphical User Interface (GUI) and command line components to manipulate servers and workstations using a scripting language that offers easy syntax. PowerShell works simply by invoking cmdlets and scripts locally or remotely. PowerShell uses the background Intelligent Transfer Service (BITS) to transfer files between machines in an asynchronized and prioritized manner. PowerShell has several advantages, including the ability to execute powerful scripts to accomplish tasks that cannot be executed using a few lines of code. Further, PowerShell variables can hold output from values, commands, and objects, and it is not necessary to specify the type of a particular variable. PowerShell can be used as a scripting language to automate the management of systems and to deploy solutions in continuous integration/continuous delivery (CI/CD) environments. PowerShell scripting language is fully extensible with its classes, modules, scripts, and functions.