Hands On Gpu Accelerated Computer Vision With Opencv And Cuda

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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA

Author : Bhaumik Vaidya
Publisher : Packt Publishing Ltd
ISBN 13 : 1789343682
Total Pages : 373 pages
Book Rating : 4.7/5 (893 download)

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Book Synopsis Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA by : Bhaumik Vaidya

Download or read book Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA written by Bhaumik Vaidya and published by Packt Publishing Ltd. This book was released on 2018-09-26 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how CUDA allows OpenCV to handle complex and rapidly growing image data processing in computer and machine vision by accessing the power of GPU Key FeaturesExplore examples to leverage the GPU processing power with OpenCV and CUDAEnhance the performance of algorithms on embedded hardware platformsDiscover C++ and Python libraries for GPU accelerationBook Description Computer vision has been revolutionizing a wide range of industries, and OpenCV is the most widely chosen tool for computer vision with its ability to work in multiple programming languages. Nowadays, in computer vision, there is a need to process large images in real time, which is difficult to handle for OpenCV on its own. This is where CUDA comes into the picture, allowing OpenCV to leverage powerful NVDIA GPUs. This book provides a detailed overview of integrating OpenCV with CUDA for practical applications. To start with, you’ll understand GPU programming with CUDA, an essential aspect for computer vision developers who have never worked with GPUs. You’ll then move on to exploring OpenCV acceleration with GPUs and CUDA by walking through some practical examples. Once you have got to grips with the core concepts, you’ll familiarize yourself with deploying OpenCV applications on NVIDIA Jetson TX1, which is popular for computer vision and deep learning applications. The last chapters of the book explain PyCUDA, a Python library that leverages the power of CUDA and GPUs for accelerations and can be used by computer vision developers who use OpenCV with Python. By the end of this book, you’ll have enhanced computer vision applications with the help of this book's hands-on approach. What you will learnUnderstand how to access GPU device properties and capabilities from CUDA programsLearn how to accelerate searching and sorting algorithmsDetect shapes such as lines and circles in imagesExplore object tracking and detection with algorithmsProcess videos using different video analysis techniques in Jetson TX1Access GPU device properties from the PyCUDA programUnderstand how kernel execution worksWho this book is for This book is a go-to guide for you if you are a developer working with OpenCV and want to learn how to process more complex image data by exploiting GPU processing. A thorough understanding of computer vision concepts and programming languages such as C++ or Python is expected.

Hands-On GPU Programming with Python and CUDA

Author : Dr. Brian Tuomanen
Publisher : Packt Publishing Ltd
ISBN 13 : 1788995228
Total Pages : 300 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Hands-On GPU Programming with Python and CUDA by : Dr. Brian Tuomanen

Download or read book Hands-On GPU Programming with Python and CUDA written by Dr. Brian Tuomanen and published by Packt Publishing Ltd. This book was released on 2018-11-27 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build real-world applications with Python 2.7, CUDA 9, and CUDA 10. We suggest the use of Python 2.7 over Python 3.x, since Python 2.7 has stable support across all the libraries we use in this book. Key FeaturesExpand your background in GPU programming—PyCUDA, scikit-cuda, and NsightEffectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolverApply GPU programming to modern data science applicationsBook Description Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler to identify bottlenecks in your Python code, and set up an appropriate GPU programming environment. You’ll then see how to “query” the GPU’s features and copy arrays of data to and from the GPU’s own memory. As you make your way through the book, you’ll launch code directly onto the GPU and write full blown GPU kernels and device functions in CUDA C. You’ll get to grips with profiling GPU code effectively and fully test and debug your code using Nsight IDE. Next, you’ll explore some of the more well-known NVIDIA libraries, such as cuFFT and cuBLAS. With a solid background in place, you will now apply your new-found knowledge to develop your very own GPU-based deep neural network from scratch. You’ll then explore advanced topics, such as warp shuffling, dynamic parallelism, and PTX assembly. In the final chapter, you’ll see some topics and applications related to GPU programming that you may wish to pursue, including AI, graphics, and blockchain. By the end of this book, you will be able to apply GPU programming to problems related to data science and high-performance computing. What you will learnLaunch GPU code directly from PythonWrite effective and efficient GPU kernels and device functionsUse libraries such as cuFFT, cuBLAS, and cuSolverDebug and profile your code with Nsight and Visual ProfilerApply GPU programming to datascience problemsBuild a GPU-based deep neuralnetwork from scratchExplore advanced GPU hardware features, such as warp shufflingWho this book is for Hands-On GPU Programming with Python and CUDA is for developers and data scientists who want to learn the basics of effective GPU programming to improve performance using Python code. You should have an understanding of first-year college or university-level engineering mathematics and physics, and have some experience with Python as well as in any C-based programming language such as C, C++, Go, or Java.

Hands-On GPU Computing with Python

Author : Avimanyu Bandyopadhyay
Publisher : Packt Publishing Ltd
ISBN 13 : 1789342406
Total Pages : 441 pages
Book Rating : 4.7/5 (893 download)

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Book Synopsis Hands-On GPU Computing with Python by : Avimanyu Bandyopadhyay

Download or read book Hands-On GPU Computing with Python written by Avimanyu Bandyopadhyay and published by Packt Publishing Ltd. This book was released on 2019-05-14 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate Key FeaturesUnderstand effective synchronization strategies for faster processing using GPUsWrite parallel processing scripts with PyCuda and PyOpenCLLearn to use the CUDA libraries like CuDNN for deep learning on GPUsBook Description GPUs are proving to be excellent general purpose-parallel computing solutions for high performance tasks such as deep learning and scientific computing. This book will be your guide to getting started with GPU computing. It will start with introducing GPU computing and explain the architecture and programming models for GPUs. You will learn, by example, how to perform GPU programming with Python, and you’ll look at using integrations such as PyCUDA, PyOpenCL, CuPy and Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance. By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly. What you will learnUtilize Python libraries and frameworks for GPU accelerationSet up a GPU-enabled programmable machine learning environment on your system with AnacondaDeploy your machine learning system on cloud containers with illustrated examplesExplore PyCUDA and PyOpenCL and compare them with platforms such as CUDA, OpenCL and ROCm.Perform data mining tasks with machine learning models on GPUsExtend your knowledge of GPU computing in scientific applicationsWho this book is for Data Scientist, Machine Learning enthusiasts and professionals who wants to get started with GPU computation and perform the complex tasks with low-latency. Intermediate knowledge of Python programming is assumed.

Hands-On GPU Programming with CUDA

Author : Jaegeun Han
Publisher :
ISBN 13 : 9781788996242
Total Pages : 508 pages
Book Rating : 4.9/5 (962 download)

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Book Synopsis Hands-On GPU Programming with CUDA by : Jaegeun Han

Download or read book Hands-On GPU Programming with CUDA written by Jaegeun Han and published by . This book was released on 2019-09-27 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore different GPU programming methods using libraries and directives, such as OpenACC, with extension to languages such as C, C++, and Python Key Features Learn parallel programming principles and practices and performance analysis in GPU computing Get to grips with distributed multi GPU programming and other approaches to GPU programming Understand how GPU acceleration in deep learning models can improve their performance Book Description Compute Unified Device Architecture (CUDA) is NVIDIA's GPU computing platform and application programming interface. It's designed to work with programming languages such as C, C++, and Python. With CUDA, you can leverage a GPU's parallel computing power for a range of high-performance computing applications in the fields of science, healthcare, and deep learning. Learn CUDA Programming will help you learn GPU parallel programming and understand its modern applications. In this book, you'll discover CUDA programming approaches for modern GPU architectures. You'll not only be guided through GPU features, tools, and APIs, you'll also learn how to analyze performance with sample parallel programming algorithms. This book will help you optimize the performance of your apps by giving insights into CUDA programming platforms with various libraries, compiler directives (OpenACC), and other languages. As you progress, you'll learn how additional computing power can be generated using multiple GPUs in a box or in multiple boxes. Finally, you'll explore how CUDA accelerates deep learning algorithms, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). By the end of this CUDA book, you'll be equipped with the skills you need to integrate the power of GPU computing in your applications. What you will learn Understand general GPU operations and programming patterns in CUDA Uncover the difference between GPU programming and CPU programming Analyze GPU application performance and implement optimization strategies Explore GPU programming, profiling, and debugging tools Grasp parallel programming algorithms and how to implement them Scale GPU-accelerated applications with multi-GPU and multi-nodes Delve into GPU programming platforms with accelerated libraries, Python, and OpenACC Gain insights into deep learning accelerators in CNNs and RNNs using GPUs Who this book is for This beginner-level book is for programmers who want to delve into parallel computing, become part of the high-performance computing community and build modern applications. Basic C and C++ programming experience is assumed. For deep learning enthusiasts, this book covers Python InterOps, DL libraries, and practical examples on performance estimation.

A Practical Introduction to Computer Vision with OpenCV

Author : Kenneth Dawson-Howe
Publisher : John Wiley & Sons
ISBN 13 : 111884873X
Total Pages : 240 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis A Practical Introduction to Computer Vision with OpenCV by : Kenneth Dawson-Howe

Download or read book A Practical Introduction to Computer Vision with OpenCV written by Kenneth Dawson-Howe and published by John Wiley & Sons. This book was released on 2014-03-20 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the theory behind basic computer vision and providesa bridge from the theory to practical implementation using theindustry standard OpenCV libraries Computer Vision is a rapidly expanding area and it is becomingprogressively easier for developers to make use of this field dueto the ready availability of high quality libraries (such as OpenCV2). This text is intended to facilitate the practical use ofcomputer vision with the goal being to bridge the gap between thetheory and the practical implementation of computer vision. Thebook will explain how to use the relevant OpenCV library routinesand will be accompanied by a full working program including thecode snippets from the text. This textbook is a heavilyillustrated, practical introduction to an exciting field, theapplications of which are becoming almost ubiquitous. We arenow surrounded by cameras, for example cameras on computers &tablets/ cameras built into our mobile phones/ camerasin games consoles; cameras imaging difficult modalities (such asultrasound, X-ray, MRI) in hospitals, and surveillance cameras.This book is concerned with helping the next generation of computerdevelopers to make use of all these images in order to developsystems which are more intuitive and interact with us in moreintelligent ways. Explains the theory behind basic computer vision and provides abridge from the theory to practical implementation using theindustry standard OpenCV libraries Offers an introduction to computer vision, with enough theoryto make clear how the various algorithms work but with an emphasison practical programming issues Provides enough material for a one semester course in computervision at senior undergraduate and Masters levels Includes the basics of cameras and images and image processingto remove noise, before moving on to topics such as imagehistogramming; binary imaging; video processing to detect and modelmoving objects; geometric operations & camera models; edgedetection; features detection; recognition in images Contains a large number of vision application problems toprovide students with the opportunity to solve real problems.Images or videos for these problems are provided in the resourcesassociated with this book which include an enhanced eBook

Mastering OpenCV 4

Author : Roy Shilkrot
Publisher : Packt Publishing Ltd
ISBN 13 : 1789539269
Total Pages : 272 pages
Book Rating : 4.7/5 (895 download)

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Book Synopsis Mastering OpenCV 4 by : Roy Shilkrot

Download or read book Mastering OpenCV 4 written by Roy Shilkrot and published by Packt Publishing Ltd. This book was released on 2018-12-27 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work on practical computer vision projects covering advanced object detector techniques and modern deep learning and machine learning algorithms Key FeaturesLearn about the new features that help unlock the full potential of OpenCV 4Build face detection applications with a cascade classifier using face landmarksCreate an optical character recognition (OCR) model using deep learning and convolutional neural networksBook Description Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You’ll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You’ll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You’ll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4. What you will learnBuild real-world computer vision problems with working OpenCV code samplesUncover best practices in engineering and maintaining OpenCV projectsExplore algorithmic design approaches for complex computer vision tasksWork with OpenCV’s most updated API (v4.0.0) through projectsUnderstand 3D scene reconstruction and Structure from Motion (SfM)Study camera calibration and overlay AR using the ArUco ModuleWho this book is for This book is for those who have a basic knowledge of OpenCV and are competent C++ programmers. You need to have an understanding of some of the more theoretical/mathematical concepts, as we move quite quickly throughout the book.

Deep Learning for Coders with fastai and PyTorch

Author : Jeremy Howard
Publisher : O'Reilly Media
ISBN 13 : 1492045497
Total Pages : 624 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for Coders with fastai and PyTorch by : Jeremy Howard

Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Computer Vision Metrics

Author : Scott Krig
Publisher : Apress
ISBN 13 : 1430259302
Total Pages : 498 pages
Book Rating : 4.4/5 (32 download)

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Book Synopsis Computer Vision Metrics by : Scott Krig

Download or read book Computer Vision Metrics written by Scott Krig and published by Apress. This book was released on 2014-06-14 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications. The survey is broader than it is deep, with over 540 references provided to dig deeper. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more. Rather than providing ‘how-to’ source code examples and shortcuts, this book provides a counterpoint discussion to the many fine opencv community source code resources available for hands-on practitioners.

Learn Computer Vision Using OpenCV

Author : Sunila Gollapudi
Publisher : Apress
ISBN 13 : 1484242610
Total Pages : 163 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Learn Computer Vision Using OpenCV by : Sunila Gollapudi

Download or read book Learn Computer Vision Using OpenCV written by Sunila Gollapudi and published by Apress. This book was released on 2019-04-26 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples. The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you’ll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision. After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work. What You Will LearnUnderstand what computer vision is, and its overall application in intelligent automation systems Discover the deep learning techniques required to build computer vision applications Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis Who This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.

Python Deep Learning Cookbook

Author : Indra den Bakker
Publisher : Packt Publishing Ltd
ISBN 13 : 1787122255
Total Pages : 321 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Python Deep Learning Cookbook by : Indra den Bakker

Download or read book Python Deep Learning Cookbook written by Indra den Bakker and published by Packt Publishing Ltd. This book was released on 2017-10-27 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide About This Book Practical recipes on training different neural network models and tuning them for optimal performance Use Python frameworks like TensorFlow, Caffe, Keras, Theano for Natural Language Processing, Computer Vision, and more A hands-on guide covering the common as well as the not so common problems in deep learning using Python Who This Book Is For This book is intended for machine learning professionals who are looking to use deep learning algorithms to create real-world applications using Python. Thorough understanding of the machine learning concepts and Python libraries such as NumPy, SciPy and scikit-learn is expected. Additionally, basic knowledge in linear algebra and calculus is desired. What You Will Learn Implement different neural network models in Python Select the best Python framework for deep learning such as PyTorch, Tensorflow, MXNet and Keras Apply tips and tricks related to neural networks internals, to boost learning performances Consolidate machine learning principles and apply them in the deep learning field Reuse and adapt Python code snippets to everyday problems Evaluate the cost/benefits and performance implication of each discussed solution In Detail Deep Learning is revolutionizing a wide range of industries. For many applications, deep learning has proven to outperform humans by making faster and more accurate predictions. This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. These applications include Computer Vision, Natural Language Processing, Time Series, and Robotics. The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, PyTorch, Keras and CNTK is provided. The book includes recipes that are related to the basic concepts of neural networks. All techniques s, as well as classical networks topologies. The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios. Style and approach Unique blend of independent recipes arranged in the most logical manner

CUDA Application Design and Development

Author : Rob Farber
Publisher : Elsevier
ISBN 13 : 0123884268
Total Pages : 338 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis CUDA Application Design and Development by : Rob Farber

Download or read book CUDA Application Design and Development written by Rob Farber and published by Elsevier. This book was released on 2011-10-31 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book then details the thought behind CUDA and teaches how to create, analyze, and debug CUDA applications. Throughout, the focus is on software engineering issues: how to use CUDA in the context of existing application code, with existing compilers, languages, software tools, and industry-standard API libraries."--Pub. desc.

Programming Massively Parallel Processors

Author : David B. Kirk
Publisher : Newnes
ISBN 13 : 0123914183
Total Pages : 514 pages
Book Rating : 4.1/5 (239 download)

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Book Synopsis Programming Massively Parallel Processors by : David B. Kirk

Download or read book Programming Massively Parallel Processors written by David B. Kirk and published by Newnes. This book was released on 2012-12-31 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing

Second International Conference on Computer Networks and Communication Technologies

Author : S. Smys
Publisher : Springer Nature
ISBN 13 : 3030370518
Total Pages : 968 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Second International Conference on Computer Networks and Communication Technologies by : S. Smys

Download or read book Second International Conference on Computer Networks and Communication Technologies written by S. Smys and published by Springer Nature. This book was released on 2020-01-21 with total page 968 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents new communication and networking technologies, an area that has gained significant research attention from both academia and industry in recent years. It also discusses the development of more intelligent and efficient communication technologies, which are an essential part of current day-to-day life, and reports on recent innovations in technologies, architectures, and standards relating to these technologies. The book includes research that spans a wide range of communication and networking technologies, including wireless sensor networks, big data, Internet of Things, optical and telecommunication networks, artificial intelligence, cryptography, next-generation networks, cloud computing, and natural language processing. Moreover, it focuses on novel solutions in the context of communication and networking challenges, such as optimization algorithms, network interoperability, scalable network clustering, multicasting and fault-tolerant techniques, network authentication mechanisms, and predictive analytics.

Deep Learning with Azure

Author : Mathew Salvaris
Publisher : Apress
ISBN 13 : 1484236793
Total Pages : 298 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Deep Learning with Azure by : Mathew Salvaris

Download or read book Deep Learning with Azure written by Mathew Salvaris and published by Apress. This book was released on 2018-08-24 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI? Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll Learn Become familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AI Use pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more) Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolving Discover the options for training and operationalizing deep learning models on Azure Who This Book Is For Professional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful.

Pattern Recognition

Author : Karina Mariela Figueroa Mora
Publisher : Springer Nature
ISBN 13 : 3030490769
Total Pages : 348 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Pattern Recognition by : Karina Mariela Figueroa Mora

Download or read book Pattern Recognition written by Karina Mariela Figueroa Mora and published by Springer Nature. This book was released on 2020-06-17 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 12th Mexican Conference on Pattern Recognition, MCPR 2020, which was due to be held in Morelia, Mexico, in June 2020. The conference was held virtually due to the COVID-19 pandemic. The 31 papers presented in this volume were carefully reviewed and selected from 67 submissions. They were organized in the following topical sections: pattern recognition techniques; image processing and analysis; computer vision; industrial and medical applications of pattern recognition; natural language processing and recognition; artificial intelligence techniques and recognition.

Embedded Vision

Author : S. R. Vijayalakshmi
Publisher :
ISBN 13 : 9781683924579
Total Pages : 0 pages
Book Rating : 4.9/5 (245 download)

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Book Synopsis Embedded Vision by : S. R. Vijayalakshmi

Download or read book Embedded Vision written by S. R. Vijayalakshmi and published by . This book was released on 2019-08-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory guide for anyone who is interested in designing machines that have vision-enabled, embedded products, this book covers topics encountered in hardware architecture, software algorithms, applications, advancements in processors and sensors. --

Hands-On Embedded Programming with Qt

Author : John Werner
Publisher : Packt Publishing Ltd
ISBN 13 : 1789953804
Total Pages : 400 pages
Book Rating : 4.7/5 (899 download)

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Book Synopsis Hands-On Embedded Programming with Qt by : John Werner

Download or read book Hands-On Embedded Programming with Qt written by John Werner and published by Packt Publishing Ltd. This book was released on 2019-07-12 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide that will get you up and running with embedded software development using Qt5 Key FeaturesLearn to create fluid, cross-platform applications for embedded devicesAchieve optimum performance in your applications with QT Lite projectExplore the implementation of Qt with IoT using QtMqtt, QtKNX, and QtWebSocketsBook Description Qt is an open-source toolkit suitable for cross-platform and embedded application development. This book uses inductive teaching to help you learn how to create applications for embedded and Internet of Things (IoT) devices with Qt 5. You’ll start by learning to develop your very first application with Qt. Next, you’ll build on the first application by understanding new concepts through hands-on projects and written text. Each project will introduce new features that will help you transform your basic first project into a connected IoT application running on embedded hardware. In addition to practical experience in developing an embedded Qt project, you will also gain valuable insights into best practices for Qt development, along with exploring advanced techniques for testing, debugging, and monitoring the performance of Qt applications. Through the course of the book, the examples and projects are demonstrated in a way so that they can be run both locally and on an embedded platform. By the end of this book, you will have the skills you need to use Qt 5 to confidently develop modern embedded applications. What you will learnUnderstand how to develop Qt applications using Qt Creator under LinuxExplore various Qt GUI technologies to build resourceful and interactive applicationsUnderstand Qt’s threading model to maintain a responsive UIGet to grips with remote target load and debug under Qt CreatorBecome adept at writing IoT code using QtLearn a variety of software best practices to ensure that your code is efficientWho this book is for This book is for software and hardware professionals with experience in different domains who are seeking new career opportunities in embedded systems and IoT. Working knowledge of the C++ Linux command line will be useful to get the most out of this book.