Описание: This book presents many valuable tips for making decisions related to traffic flow in transport networks. The knowledge base in practical examples, as well as the decision support systems described in this book, finds interest among people who face the daily challenge of searching for advanced solutions and practical applications in road traffic engineering. The publication is therefore addressed to local authorities related to the planning and development of development strategies for selected areas with regard to transport (both in the urban and regional dimension) and to representatives of business and industry, as people directly involved in the implementation of traffic engineering solutions. The publication contains selected papers submitted to and presented at the 18th “Transport Systems. Theory and Practice” Scientific and Technical Conference organized by the Department of Transport Systems, Traffic Engineering and Logistics at the Faculty of Transport and Aviation Engineering at the Silesian University of Technology. The conference took place on September 19-20, 2022, in Katowice (Poland).
Автор: Ratten, Vanessa (La Trobe University, Australia) Название: Practical Artificial Intelligence for Internet of Medical Things ISBN: 1032325275 ISBN-13(EAN): 9781032325279 Издательство: Taylor&Francis Рейтинг: Цена: 21437.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers the fundamentals, applications, algorithms, protocols, emerging trends, problems, and research findings in the field of AI and IoT in smart healthcare. It includes working examples, case studies, implementation and management of smart healthcare systems using AI.
Автор: Kim, Phil Название: Matlab deep learning ISBN: 1484228448 ISBN-13(EAN): 9781484228449 Издательство: Springer Рейтинг: Цена: 4634.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Starting with machine learning fundamentals, this book moves on to neural networks, deep learning, and convolutional neural networks, using MATLAB as the underlying programming language and tool for examples and case studies in this book to tackle some of today`s real world big data, smart bots, and other complex data problems.
Автор: Haughian, Barry Название: Design, launch, and scale iot services ISBN: 1484237110 ISBN-13(EAN): 9781484237113 Издательство: Springer Рейтинг: Цена: 4024.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The Internet of Things is causing major industry disruption, so companies need to plan and manage their “IoT journey” to maximize all business opportunities. In this book companies can learn how to successfully create, launch and manage Internet of Things services.
It takes the reader through the process of specifying, implementing, and deploying IoT services; detailing how to scale and manage an IoT business. It introduces the fundamentals of IoT services, explaining IoT service building blocks and the key factors to be considered in the design of IoT services.
Moving into the IoT field requires speed. This book provides a fast track approach to IoT; summarizing the global experiences of the author, detailing the discussions, mistakes, successes, learnings and conclusions. Building an Internet of Things Service enables readers to accelerate their own on-boarding in their IoT journey.
What You'll Learn
Create new IoT ServicesReview the basic IoT concepts and business implications you need to know as you embark on your IoT journeySolve the major challenges presented by the IoT disruption.Accelerate your own on-boarding in their IoT journey.
Who This Book Is For
The primary audience is made up of business executives and IoT startups. The secondary audience is students studying IoT in universities and those interested in understanding the fundamentals of an IoT business. No technical background is required.
Автор: Li Название: Theory of Practical Cellular Automaton ISBN: 9811074968 ISBN-13(EAN): 9789811074967 Издательство: Springer Рейтинг: Цена: 19514.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the intellectual foundations, function, modeling approaches and complexity of cellular automata; explores cellular automata in combination with genetic algorithms, neural networks and agents; and discusses the applications of cellular automata in economics, traffic and the spread of disease.
Описание: Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challenges in time series, using both traditional statistical and modern machine learning techniques.
Автор: Irfan Turk Название: Practical MATLAB ISBN: 1484252802 ISBN-13(EAN): 9781484252802 Издательство: Springer Рейтинг: Цена: 7927.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Apply MATLAB programming to the mathematical modeling of real-life problems from a wide range of topics. This pragmatic book shows you how to solve your programming problems, starting with a brief primer on MATLAB and the fundamentals of the MATLAB programming language. Then, you’ll build fully working examples and computational models found in the financial, engineering, and scientific sectors. As part of this section, you’ll cover signal and image processing, as well as GUIs.
After reading and using Practical MATLAB and its accompanying source code, you’ll have the practical know-how and code to apply to your own MATLAB programming projects.
What You Will Learn
Discover the fundamentals of MATLAB and how to get started with it for problem solvingApply MATLAB to a variety of problems and case studiesCarry out economic and financial modeling with MATLAB, including option pricing and compound interestUse MATLAB for simulation problems such as coin flips, dice rolling, random walks, and traffic flowsSolve computational biology problems with MATLABImplement signal processing with MATLAB, including currents, Fast Fourier Transforms (FFTs), and harmonic analysisProcess images with filters and edge detectionBuild applications with GUIs
Who This Book Is For
People with some prior experience with programming and MATLAB.
Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms.
For automating the process, the book highlights the limitations of traditional hand-crafted features for computer vision and why the CNN deep-learning model is the state-of-art solution. CNNs are discussed from scratch to demonstrate how they are different and more efficient than the fully connected ANN (FCNN). You will implement a CNN in Python to give you a full understanding of the model.
After consolidating the basics, you will use TensorFlow to build a practical image-recognition model that you will deploy to a web server using Flask, making it accessible over the Internet. Using Kivy and NumPy, you will create cross-platform data science applications with low overheads.
This book will help you apply deep learning and computer vision concepts from scratch, step-by-step from conception to production.
What You Will Learn
Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using PythonFollow a deep learning project from conception to production using TensorFlowUse NumPy with Kivy to build cross-platform data science applications
Who This Book Is For
Data scientists, machine learning and deep learning engineers, software developers.
Автор: Rivera, Juan De Dios Santos Название: Practical tensorflow.js ISBN: 1484262727 ISBN-13(EAN): 9781484262726 Издательство: Springer Рейтинг: Цена: 7927.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Develop and deploy deep learning web apps using the TensorFlow.js library. TensorFlow.js is part of a bigger framework named TensorFlow, which has many tools that supplement it, such as TensorBoard, ml5js, tfjs-vis. This book will cover all these technologies and show they integrate with TensorFlow.js to create intelligent web apps. The most common and accessible platform users interact with everyday is their web browser, making it an ideal environment to deploy AI systems. TensorFlow.js is a well-known and battle-tested library for creating browser solutions. Working in JavaScript, the so-called language of the web, directly on a browser, you can develop and serve deep learning applications.You'll work with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN). Through hands-on examples, apply these networks in use cases related to image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis. Also, these topics are very varied in terms of the kind of data they use, their output, and the training phase. Not everything in machine learning is deep networks, there is also what some call shallow or traditional machine learning. While TensorFlow.js is not the most common place to implement these, you'll be introduce them and review the basics of machine learning through TensorFlow.js. What You'll Learn
Build deep learning products suitable for web browsers
Work with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN)
Develop apps using image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis
Who This Book Is For Programmers developing deep learning solutions for the web and those who want to learn TensorFlow.js with at least minimal programming and software development knowledge. No prior JavaScript knowledge is required, but familiarity with it is helpful.
Implement various state-of-the-art architectures, such as GANs and autoencoders, for image generation using TensorFlow 2.x from scratch
Key Features
Understand the different architectures for image generation, including autoencoders and GANs
Build models that can edit an image of your face, turn photos into paintings, and generate photorealistic images
Discover how you can build deep neural networks with advanced TensorFlow 2.x features
Book Description
The emerging field of Generative Adversarial Networks (GANs) has made it possible to generate indistinguishable images from existing datasets. With this hands-on book, you'll not only develop image generation skills but also gain a solid understanding of the underlying principles.
Starting with an introduction to the fundamentals of image generation using TensorFlow, this book covers Variational Autoencoders (VAEs) and GANs. You'll discover how to build models for different applications as you get to grips with performing face swaps using deepfakes, neural style transfer, image-to-image translation, turning simple images into photorealistic images, and much more. You'll also understand how and why to construct state-of-the-art deep neural networks using advanced techniques such as spectral normalization and self-attention layer before working with advanced models for face generation and editing. You'll also be introduced to photo restoration, text-to-image synthesis, video retargeting, and neural rendering. Throughout the book, you'll learn to implement models from scratch in TensorFlow 2.x, including PixelCNN, VAE, DCGAN, WGAN, pix2pix, CycleGAN, StyleGAN, GauGAN, and BigGAN.
By the end of this book, you'll be well versed in TensorFlow and be able to implement image generative technologies confidently.
What You Will Learn
Train on face datasets and use them to explore latent spaces for editing new faces
Get to grips with swapping faces with deepfakes
Perform style transfer to convert a photo into a painting
Build and train pix2pix, CycleGAN, and BicycleGAN for image-to-image translation
Use iGAN to understand manifold interpolation and GauGAN to turn simple images into photorealistic images
Become well versed in attention generative models such as SAGAN and BigGAN
Generate high-resolution photos with Progressive GAN and StyleGAN
Who this book is for
The Hands-On Image Generation with TensorFlow book is for deep learning engineers, practitioners, and researchers who have basic knowledge of convolutional neural networks and want to learn various image generation techniques using TensorFlow 2.x. You'll also find this book useful if you are an image processing professional or computer vision engineer looking to explore state-of-the-art architectures to improve and enhance images and videos. Knowledge of Python and TensorFlow will help you to get the best out of this book.
Автор: Seneque Gareth, Chua Darrell Название: Hands-On Deep Learning with Go ISBN: 1789340993 ISBN-13(EAN): 9781789340990 Издательство: Неизвестно Рейтинг: Цена: 9378.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Go ecosystem comprises some really powerful Deep Learning tools. This book shows you how to use these tools to train and deploy scalable Deep Learning models. You will explore a number of modern Neural Network architectures such as CNNs, RNNs, and more. By the end, you will be able to train your own Deep Learning models from scratch, using ...
Описание: Deep learning enables efficient and accurate learning from data. Developers working with R will be able to put their knowledge to work with this practical guide to deep learning. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time.
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