Visual information retrieval (VIR) is an active and vibrant research area, which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) from large, unstructured repositories. The goal of VIR is to retrieve matches ranked by their relevance to a given query, which is often expressed as an example image and/or a series of keywords. During its early years (1995-2000), the research efforts were dominated by content-based approach...

Visual information retrieval (VIR) is an active and vibrant research area, which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) from large, unstructured repositories. The goal of VIR is to retrieve matches ranked by their relevance to a given query, which is often expressed as an example image and/or a series of keywords. During its early years (1995-2000), the research efforts were dominated by content-based approach...

Publisher's Note: This edition from 2017 is outdated and not compatible with TensorFlow 2.x or any of the most recent updates to Python libraries. A new edition completely updated and revised for 2020 with seven additional chapters that cover RNNs, AI and big data, fundamental use cases, chatbots, and more, is now available. Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you. Key FeaturesStep int...

Each chapter of the book quickly introduces a key theme of Data Analysis, before immersing you in the practical aspects of each theme. Youll learn quickly how to perform all aspects of Data Analysis.Practical Data Analysis is a book ideal for home and small business users who want to slice & dice the data they have on hand with minimum hassle.

Dive into the future of data science and learn how to build the sophisticated algorithms that are fundamental to deep learning and AI with JavaKey Features\[\*\] Go beyond the theory and put Deep Learning into practice with Java\[\*\]Find out how to build a range of Deep Learning algorithms using a range of leading frameworks including DL4J, Theano and Caffe\[\*\] Whether you’re a data scientist or Java developer, dive in and find out how to ta...

Here’s what three pioneers in computer graphics and human-computer interaction have to say about this book:“What a tour de force—everything one would want—comprehensive, encyclopedic, and authoritative.”—Jim Foley“At last, a book on this important, emerging area. It will be an indispensable reference for the practitioner, researcher, and student interested in 3D user interfaces.”

Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x Key FeaturesSkill up and implement tricky neural networks using Google's TensorFlow 1.xAn easy-to-follow guide that lets you explore reinforcement learning, GANs, autoencoders, multilayer perceptrons and more.Hands-on recipes to work with Tensorflow on desktop, mobile, and cloud environmentBook DescriptionDeep neural networ...

Key FeaturesBook DescriptionDesign and develop advanced computer vision projects using OpenCV with Python About This Book Program advanced computer vision applications in Python using different features of the OpenCV library Practical end-to-end project covering an important computer vision problem All projects in the book include a step-by-step guide to create computer vision applications Who This Book Is For This book is for intermediate users of Ope...

Build, implement and scale distributed deep learning models for large-scale datasets Key FeaturesGet to grips with the deep learning concepts and set up Hadoop to put them to useImplement and parallelize deep learning models on Hadoop’s YARN frameworkA comprehensive tutorial to distributed deep learning with HadoopBook DescriptionThis book will teach you how to deploy large-scale dataset in deep neural networks with Hadoop fo...

This comprehensive text/reference examines in depth the synergy between multimedia content analysis, personalization, and next-generation networking. The book demonstrates how this integration can result in robust, personalized services that provide users with an improved multimedia-centric quality of experience. Each chapter offers a practical step-by-step walkthrough for a variety of concepts, components and technologies relating to the development of applications and services. Topics an...

Written specifically for those with no prior programming experience and minimal quantitative training, this accessible text walks behavioral science students and researchers through the process of programming using MATLAB. The book explores examples, terms, and programming needs relevant to those in the behavioral sciences and helps readers perform virtually any computational function in solving their research problems. Principles are illustrated with usable code. Each chapter opens with a...

100 recipes that teach you how to perform various machine learning tasks in the real worldKey Features\[\*\]Understand which algorithms to use in a given context with the help of this exciting recipe-based guide\[\*\]Learn about perceptrons and see how they are used to build neural networks\[\*\]Stuck while making sense of images, text, speech, and real estate? This guide will come to your rescue, showing you how to perform machine learning for...