Author: Alvin Yang
Publisher: Springer
ISBN: 331994472X
Category : Computers
Languages : en
Pages : 187
Book Description
This book constitutes the refereed proceedings of the 14th World Congress on Services, SERVICES 2018, held as part of the Services Conference Federation, SCF 2018, in Seattle, USA, in June 2018. The 10 full papers and 3 short papers presented were carefully reviewed and selected from 22 submissions. The papers cover topics in the field of software foundations and applications with a focus on novel approaches for engineering requirements, design and architectures, testing, maintenance and evolution, model-driven development, software processes, metrics, quality assurance and new software economics models, search-based software engineering, benefiting day-to-day services sectors and derived through experiences, with appreciation to scale, pragmatism, transparency, compliance and/or dependability.
Computer Vision for the Web
Author: Foat Akhmadeev
Publisher: Packt Publishing Ltd
ISBN: 1785889877
Category : Computers
Languages : en
Pages : 116
Book Description
Unleash the power of the Computer Vision algorithms in JavaScript to develop vision-enabled web content About This Book Explore the exciting world of image processing, and face and gesture recognition, and implement them in your website Develop wonderful web projects to implement Computer Vision algorithms in an effective way A fast-paced guide to help you deal with real-world Computer Vision applications using JavaScript libraries Who This Book Is For If you have an interest in Computer Vision or wish to apply Computer Vision algorithms such as face, custom object, and gesture recognition for an online application, then this book is ideal for you. Prior understanding of the JavaScript language and core mathematical concepts is recommended. What You Will Learn Apply complex Computer Vision algorithms in your applications using JavaScript Put together different JavaScript libraries to discover objects in photos Get to grips with developing simple computer vision applications on your own Understand when and why you should use different computer vision methods Apply various image filters to images and videos Recognize and track many different objects, including face and face particles using powerful face recognition algorithms Explore ways to control your browser without touching the mouse or keyboard In Detail JavaScript is a dynamic and prototype-based programming language supported by every browser today. JavaScript libraries boast outstanding functionalities that enable you to furnish your own Computer Vision projects, making it easier to develop JavaScript–based applications, especially for web-centric technologies. It makes the implementation of Computer Vision algorithms easier as it supports scheme-based functional programming. This book will give you an insight into controlling your applications with gestures and head motion and readying them for the web. Packed with real-world tasks, it begins with a walkthrough of the basic concepts of Computer Vision that the JavaScript world offers us, and you'll implement various powerful algorithms in your own online application. Then, we move on to a comprehensive analysis of JavaScript functions and their applications. Furthermore, the book will show you how to implement filters and image segmentation, and use tracking.js and jsfeat libraries to convert your browser into Photoshop. Subjects such as object and custom detection, feature extraction, and object matching are covered to help you find an object in a photo. You will see how a complex object such as a face can be recognized by a browser as you move toward the end of the book. Finally, you will focus on algorithms to create a human interface. By the end of this book, you will be familiarized with the application of complex Computer Vision algorithms to develop your own applications, without spending much time learning sophisticated theory. Style and approach This book is an easy-to-follow project-based guide that throws you directly into the excitement of the Computer Vision theme. A “more in less” approach is followed by important concepts explained in a to-the-point, easy-to-understand manner.
Publisher: Packt Publishing Ltd
ISBN: 1785889877
Category : Computers
Languages : en
Pages : 116
Book Description
Unleash the power of the Computer Vision algorithms in JavaScript to develop vision-enabled web content About This Book Explore the exciting world of image processing, and face and gesture recognition, and implement them in your website Develop wonderful web projects to implement Computer Vision algorithms in an effective way A fast-paced guide to help you deal with real-world Computer Vision applications using JavaScript libraries Who This Book Is For If you have an interest in Computer Vision or wish to apply Computer Vision algorithms such as face, custom object, and gesture recognition for an online application, then this book is ideal for you. Prior understanding of the JavaScript language and core mathematical concepts is recommended. What You Will Learn Apply complex Computer Vision algorithms in your applications using JavaScript Put together different JavaScript libraries to discover objects in photos Get to grips with developing simple computer vision applications on your own Understand when and why you should use different computer vision methods Apply various image filters to images and videos Recognize and track many different objects, including face and face particles using powerful face recognition algorithms Explore ways to control your browser without touching the mouse or keyboard In Detail JavaScript is a dynamic and prototype-based programming language supported by every browser today. JavaScript libraries boast outstanding functionalities that enable you to furnish your own Computer Vision projects, making it easier to develop JavaScript–based applications, especially for web-centric technologies. It makes the implementation of Computer Vision algorithms easier as it supports scheme-based functional programming. This book will give you an insight into controlling your applications with gestures and head motion and readying them for the web. Packed with real-world tasks, it begins with a walkthrough of the basic concepts of Computer Vision that the JavaScript world offers us, and you'll implement various powerful algorithms in your own online application. Then, we move on to a comprehensive analysis of JavaScript functions and their applications. Furthermore, the book will show you how to implement filters and image segmentation, and use tracking.js and jsfeat libraries to convert your browser into Photoshop. Subjects such as object and custom detection, feature extraction, and object matching are covered to help you find an object in a photo. You will see how a complex object such as a face can be recognized by a browser as you move toward the end of the book. Finally, you will focus on algorithms to create a human interface. By the end of this book, you will be familiarized with the application of complex Computer Vision algorithms to develop your own applications, without spending much time learning sophisticated theory. Style and approach This book is an easy-to-follow project-based guide that throws you directly into the excitement of the Computer Vision theme. A “more in less” approach is followed by important concepts explained in a to-the-point, easy-to-understand manner.
Computer Vision and Internet of Things
Author: Lavanya Sharma
Publisher: CRC Press
ISBN: 100057055X
Category : Computers
Languages : en
Pages : 319
Book Description
Computer Vision and Internet of Things: Technologies and Applications explores the utilization of Internet of Things (IoT) with computer vision and its underlying technologies in different applications areas. Using a series of present and future applications – including business insights, indoor-outdoor securities, smart grids, human detection and tracking, intelligent traffic monitoring, e-health departments, and medical imaging – this book focuses on providing a detailed description of the utilization of IoT with computer vision and its underlying technologies in critical application areas, such as smart grids, emergency departments, intelligent traffic cams, insurance, and the automotive industry. Key Features • Covers the challenging issues related to sensors, detection, and tracking of moving objects with solutions to handle relevant challenges • Describes the latest technological advances in IoT and computer vision with their implementations • Combines image processing and analysis into a unified framework to understand both IOT and computer vision applications • Explores mining and tracking of motion-based object data, such as trajectory prediction and prediction of a particular location of object data, and their critical applications • Provides novel solutions for medical imaging (skin lesion detection, cancer detection, enhancement techniques for MRI images, and automated disease prediction) This book is primarily aimed at graduates and researchers working in the areas of IoT, computer vision, big data, cloud computing, and remote sensing. It is also an ideal resource for IT professionals and technology developers.
Publisher: CRC Press
ISBN: 100057055X
Category : Computers
Languages : en
Pages : 319
Book Description
Computer Vision and Internet of Things: Technologies and Applications explores the utilization of Internet of Things (IoT) with computer vision and its underlying technologies in different applications areas. Using a series of present and future applications – including business insights, indoor-outdoor securities, smart grids, human detection and tracking, intelligent traffic monitoring, e-health departments, and medical imaging – this book focuses on providing a detailed description of the utilization of IoT with computer vision and its underlying technologies in critical application areas, such as smart grids, emergency departments, intelligent traffic cams, insurance, and the automotive industry. Key Features • Covers the challenging issues related to sensors, detection, and tracking of moving objects with solutions to handle relevant challenges • Describes the latest technological advances in IoT and computer vision with their implementations • Combines image processing and analysis into a unified framework to understand both IOT and computer vision applications • Explores mining and tracking of motion-based object data, such as trajectory prediction and prediction of a particular location of object data, and their critical applications • Provides novel solutions for medical imaging (skin lesion detection, cancer detection, enhancement techniques for MRI images, and automated disease prediction) This book is primarily aimed at graduates and researchers working in the areas of IoT, computer vision, big data, cloud computing, and remote sensing. It is also an ideal resource for IT professionals and technology developers.
Computer Vision and Applications
Author: Bernd Jahne
Publisher: Elsevier
ISBN: 0080502628
Category : Computers
Languages : en
Pages : 703
Book Description
Based on the highly successful 3-volume reference Handbook of Computer Vision and Applications, this concise edition covers in a single volume the entire spectrum of computer vision ranging form the imaging process to high-end algorithms and applications. This book consists of three parts, including an application gallery. - Bridges the gap between theory and practical applications - Covers modern concepts in computer vision as well as modern developments in imaging sensor technology - Presents a unique interdisciplinary approach covering different areas of modern science
Publisher: Elsevier
ISBN: 0080502628
Category : Computers
Languages : en
Pages : 703
Book Description
Based on the highly successful 3-volume reference Handbook of Computer Vision and Applications, this concise edition covers in a single volume the entire spectrum of computer vision ranging form the imaging process to high-end algorithms and applications. This book consists of three parts, including an application gallery. - Bridges the gap between theory and practical applications - Covers modern concepts in computer vision as well as modern developments in imaging sensor technology - Presents a unique interdisciplinary approach covering different areas of modern science
OpenCV 3.0 Computer Vision with Java
Author: Daniel Lélis Baggio
Publisher: Packt Publishing Ltd
ISBN: 178328398X
Category : Computers
Languages : en
Pages : 174
Book Description
OpenCV 3.0 Computer Vision with Java is a practical tutorial guide that explains fundamental tasks from computer vision while focusing on Java development. This book will teach you how to set up OpenCV for Java and handle matrices using the basic operations of image processing such as filtering and image transforms. It will also help you learn how to use Haar cascades for tracking faces and to detect foreground and background regions with the help of a Kinect device. It will even give you insights into server-side OpenCV. Each chapter is presented with several projects that are ready to use. The functionality of these projects is found in many classes that allow developers to understand computer vision principles and rapidly extend or customize the projects for their needs.
Publisher: Packt Publishing Ltd
ISBN: 178328398X
Category : Computers
Languages : en
Pages : 174
Book Description
OpenCV 3.0 Computer Vision with Java is a practical tutorial guide that explains fundamental tasks from computer vision while focusing on Java development. This book will teach you how to set up OpenCV for Java and handle matrices using the basic operations of image processing such as filtering and image transforms. It will also help you learn how to use Haar cascades for tracking faces and to detect foreground and background regions with the help of a Kinect device. It will even give you insights into server-side OpenCV. Each chapter is presented with several projects that are ready to use. The functionality of these projects is found in many classes that allow developers to understand computer vision principles and rapidly extend or customize the projects for their needs.
Practical Machine Learning for Computer Vision
Author: Valliappa Lakshmanan
Publisher: "O'Reilly Media, Inc."
ISBN: 1098102339
Category : Computers
Languages : en
Pages : 481
Book Description
This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability. Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras. You'll learn how to: Design ML architecture for computer vision tasks Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task Create an end-to-end ML pipeline to train, evaluate, deploy, and explain your model Preprocess images for data augmentation and to support learnability Incorporate explainability and responsible AI best practices Deploy image models as web services or on edge devices Monitor and manage ML models
Publisher: "O'Reilly Media, Inc."
ISBN: 1098102339
Category : Computers
Languages : en
Pages : 481
Book Description
This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability. Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras. You'll learn how to: Design ML architecture for computer vision tasks Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task Create an end-to-end ML pipeline to train, evaluate, deploy, and explain your model Preprocess images for data augmentation and to support learnability Incorporate explainability and responsible AI best practices Deploy image models as web services or on edge devices Monitor and manage ML models
Computer Vision
Author: Dana Harry Ballard
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 556
Book Description
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 556
Book Description
Services – SERVICES 2018
Author: Alvin Yang
Publisher: Springer
ISBN: 331994472X
Category : Computers
Languages : en
Pages : 187
Book Description
This book constitutes the refereed proceedings of the 14th World Congress on Services, SERVICES 2018, held as part of the Services Conference Federation, SCF 2018, in Seattle, USA, in June 2018. The 10 full papers and 3 short papers presented were carefully reviewed and selected from 22 submissions. The papers cover topics in the field of software foundations and applications with a focus on novel approaches for engineering requirements, design and architectures, testing, maintenance and evolution, model-driven development, software processes, metrics, quality assurance and new software economics models, search-based software engineering, benefiting day-to-day services sectors and derived through experiences, with appreciation to scale, pragmatism, transparency, compliance and/or dependability.
Publisher: Springer
ISBN: 331994472X
Category : Computers
Languages : en
Pages : 187
Book Description
This book constitutes the refereed proceedings of the 14th World Congress on Services, SERVICES 2018, held as part of the Services Conference Federation, SCF 2018, in Seattle, USA, in June 2018. The 10 full papers and 3 short papers presented were carefully reviewed and selected from 22 submissions. The papers cover topics in the field of software foundations and applications with a focus on novel approaches for engineering requirements, design and architectures, testing, maintenance and evolution, model-driven development, software processes, metrics, quality assurance and new software economics models, search-based software engineering, benefiting day-to-day services sectors and derived through experiences, with appreciation to scale, pragmatism, transparency, compliance and/or dependability.
Feature Extraction & Image Processing
Author: Mark Nixon
Publisher: Elsevier
ISBN: 0080556728
Category : Computers
Languages : en
Pages : 423
Book Description
Whilst other books cover a broad range of topics, Feature Extraction and Image Processing takes one of the prime targets of applied computer vision, feature extraction, and uses it to provide an essential guide to the implementation of image processing and computer vision techniques. Acting as both a source of reference and a student text, the book explains techniques and fundamentals in a clear and concise manner and helps readers to develop working techniques, with usable code provided throughout. The new edition is updated throughout in line with developments in the field, and is revised to focus on mathematical programming in Matlab. - Essential reading for engineers and students working in this cutting edge field - Ideal module text and background reference for courses in image processing and computer vision
Publisher: Elsevier
ISBN: 0080556728
Category : Computers
Languages : en
Pages : 423
Book Description
Whilst other books cover a broad range of topics, Feature Extraction and Image Processing takes one of the prime targets of applied computer vision, feature extraction, and uses it to provide an essential guide to the implementation of image processing and computer vision techniques. Acting as both a source of reference and a student text, the book explains techniques and fundamentals in a clear and concise manner and helps readers to develop working techniques, with usable code provided throughout. The new edition is updated throughout in line with developments in the field, and is revised to focus on mathematical programming in Matlab. - Essential reading for engineers and students working in this cutting edge field - Ideal module text and background reference for courses in image processing and computer vision
Computer Vision
Author: Richard Szeliski
Publisher: Springer Science & Business Media
ISBN: 1848829353
Category : Computers
Languages : en
Pages : 824
Book Description
Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
Publisher: Springer Science & Business Media
ISBN: 1848829353
Category : Computers
Languages : en
Pages : 824
Book Description
Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
Hands-On Computer Vision with TensorFlow 2
Author: Benjamin Planche
Publisher: Packt Publishing Ltd
ISBN: 1788839269
Category : Computers
Languages : en
Pages : 363
Book Description
A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more Key FeaturesDiscover how to build, train, and serve your own deep neural networks with TensorFlow 2 and KerasApply modern solutions to a wide range of applications such as object detection and video analysisLearn how to run your models on mobile devices and web pages and improve their performanceBook Description Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learnCreate your own neural networks from scratchClassify images with modern architectures including Inception and ResNetDetect and segment objects in images with YOLO, Mask R-CNN, and U-NetTackle problems faced when developing self-driving cars and facial emotion recognition systemsBoost your application's performance with transfer learning, GANs, and domain adaptationUse recurrent neural networks (RNNs) for video analysisOptimize and deploy your networks on mobile devices and in the browserWho this book is for If you're new to deep learning and have some background in Python programming and image processing, like reading/writing image files and editing pixels, this book is for you. Even if you're an expert curious about the new TensorFlow 2 features, you'll find this book useful. While some theoretical concepts require knowledge of algebra and calculus, the book covers concrete examples focused on practical applications such as visual recognition for self-driving cars and smartphone apps.
Publisher: Packt Publishing Ltd
ISBN: 1788839269
Category : Computers
Languages : en
Pages : 363
Book Description
A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more Key FeaturesDiscover how to build, train, and serve your own deep neural networks with TensorFlow 2 and KerasApply modern solutions to a wide range of applications such as object detection and video analysisLearn how to run your models on mobile devices and web pages and improve their performanceBook Description Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learnCreate your own neural networks from scratchClassify images with modern architectures including Inception and ResNetDetect and segment objects in images with YOLO, Mask R-CNN, and U-NetTackle problems faced when developing self-driving cars and facial emotion recognition systemsBoost your application's performance with transfer learning, GANs, and domain adaptationUse recurrent neural networks (RNNs) for video analysisOptimize and deploy your networks on mobile devices and in the browserWho this book is for If you're new to deep learning and have some background in Python programming and image processing, like reading/writing image files and editing pixels, this book is for you. Even if you're an expert curious about the new TensorFlow 2 features, you'll find this book useful. While some theoretical concepts require knowledge of algebra and calculus, the book covers concrete examples focused on practical applications such as visual recognition for self-driving cars and smartphone apps.