The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently.
Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.
Dr. Erich Gamma is technical director at the Software Technology Center of Object Technology International in Zurich, Switzerland. Dr. Richard Helm is a member of the Object Technology Practice Group in the IBM Consulting Group in Sydney, Australia. Dr. Ralph Johnson is a faculty member at the University of Illinois at Urbana-Champaign's Computer Science Department.
John Vlissides is a member of the research staff at the IBM T. J. Watson Research Center in Hawthorne, New York. He has practiced object-oriented technology for more than a decade as a designer, implementer, researcher, lecturer, and consultant. In addition to co-authoring Design Patterns: Elements of Reusable Object-Oriented Software, he is co-editor of the book Pattern Languages of Program Design 2 (both from Addison-Wesley). He and the other co-authors of Design Patterns are recipients of the 1998 Dr. Dobb's Journal Excellence in Programming Award.
The Essential Guide to Processing for Flash Developers takes a hands-on approach to learning Processing that builds upon your familiarity with Flash, and your experience with the ActionScript language and object-oriented programming concepts. The book offers a full series of Processing projects, structured to allow less experienced coders to get up to speed quickly, while leaving room for more experienced programmers to take the initial project concepts and build more complex applications.Includes a language primer explaining all of the Processing-specific programming theory you need to know Contains a full series of Processing projects and numerous easy-to-follow code examples Covers Processing’s Java mode, providing an easy-to-navigate bridge to programming in Java, Processing’s underlying host language
Developers have been using OpenCV library to develop computer vision applications for a long time. However, they now need a more effective tool to get the job done and in a much better and modern way. Qt is one of the major frameworks available for this task at the moment.
This book will teach you to develop applications with the combination of OpenCV 3 and Qt5, and how to create cross-platform computer vision applications. We’ll begin by introducing Qt, its IDE, and its SDK. Next you’ll learn how to use the OpenCV API to integrate both tools, and see how to configure Qt to use OpenCV. You’ll go on to build a full-fledged computer vision application throughout the book.
Later, you’ll create a stunning UI application using the Qt widgets technology, where you’ll display the images after they are processed in an efficient way. At the end of the book, you’ll learn how to convert OpenCV Mat to Qt QImage. You’ll also see how to efficiently process images to filter them, transform them, detect or track objects as well as analyze video. You’ll become better at developing OpenCV applications.What you will learn ● Get an introduction to Qt IDE and SDK ● Be introduced to OpenCV and see how to communicate between OpenCV and Qt ● Understand how to create UI using Qt Widgets ● Learn to develop cross-platform applications using OpenCV 3 and Qt 5 ● Explore the multithreaded application development features of Qt5 ● Improve OpenCV 3 application development using Qt5 ● Build, test, and deploy Qt and OpenCV apps, either dynamically or statically ● See Computer Vision technologies such as filtering and transformation of images, detecting and matching objects, template matching, object tracking, video and motion analysis, and much more ● Be introduced to QML and Qt Quick for iOS and Android application development Who this book is for
This book is for readers interested in building computer vision applications. Intermediate knowledge of C++ programming is expected. Even though no knowledge of Qt5 and OpenCV 3 is assumed, if you’re familiar with these frameworks, you’ll benefit.
This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004. The main goals of these two workshops were to promote the creation of an international object recognition community, with common datasets and evaluation procedures, to map the state of the art and identify the main open problems and opportunities for synergistic research, and to articulate the industrial and societal needs and opportunities for object recognition research worldwide.
The 30 thoroughly revised papers presented are organized in the following topical sections: recognition of specific objects, recognition of object categories, recognition of object categories with geometric relations, and joint recognition and segmentation.
Visual Languages and Applications is a comprehensive introduction to diagrammatical visual languages. This book discusses what visual programming languages are, and how such languages and their underlying foundations can be usefully applied to other fields in computer science. It also covers a broad range of contents from the underlying theory of graph grammars to the applications in various domains. Pointers to related topics and further readings are provided as well.
Visual Languages and Applications is designed as a secondary text book for upper-undergraduate-level students and graduate-level students in computer science and engineering. This volume is also suitable for practitioners and researchers in industry as a professional book.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse scikit-learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural netsApply practical code examples without acquiring excessive machine learning theory or algorithm details
At any given moment, someone struggles with the same software design problems you have. And, chances are, someone else has already solved your problem. This edition of Head First Design Patterns—now updated for Java 8—shows you the tried-and-true, road-tested patterns used by developers to create functional, elegant, reusable, and flexible software. By the time you finish this book, you’ll be able to take advantage of the best design practices and experiences of those who have fought the beast of software design and triumphed.
What’s so special about this book?
We think your time is too valuable to spend struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Design Patterns uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.
Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started.
This book is dedicated to all the machine learning and deep learning enthusiasts, data scientists, researchers, and even students who want to perform more accurate, fast machine learning operations with TensorFlow. Those with basic knowledge of programming (Python and C/C++) and math concepts who want to be introduced to the topics of machine learning will find this book useful.What You Will LearnInstall and adopt TensorFlow in your Python environment to solve mathematical problemsGet to know the basic machine and deep learning conceptsTrain and test neural networks to fit your data modelMake predictions using regression algorithmsAnalyze your data with a clustering procedureDevelop algorithms for clustering and data classificationUse GPU computing to analyze big dataIn Detail
Google's TensorFlow engine, after much fanfare, has evolved in to a robust, user-friendly, and customizable, application-grade software library of machine learning (ML) code for numerical computation and neural networks.
This book takes you through the practical software implementation of various machine learning techniques with TensorFlow. In the first few chapters, you'll gain familiarity with the framework and perform the mathematical operations required for data analysis. As you progress further, you'll learn to implement various machine learning techniques such as classification, clustering, neural networks, and deep learning through practical examples.
By the end of this book, you'll have gained hands-on experience of using TensorFlow and building classification, image recognition systems, language processing, and information retrieving systems for your application.Style and approach
Get quickly up and running with TensorFlow using this fast-paced guide. You will get to know everything that can be done with TensorFlow and we'll show you how to implement it in your environment. The examples in the book are from the core of the computation industry—something you can connect to and will find familiar.