Download or read book Image Recognition A Complete Guide 2021 Edition written by Gerardus Blokdyk and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image Recognition A Complete Guide - 2021 Edition.

Download or read book Image Recognition a Complete Guide 2019 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2019-04 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: How does your workforce performance management system support high-performance work and workforce engagement; consider workforce compensation, reward, recognition, and incentive practices; and reinforce a customer and business focus and achievement of your action plans? Are we making progress? What are the short and long-term Image Recognition goals? Is there a high likelihood that any recommendations will achieve their intended results? How do you govern and fulfill your societal responsibilities? This easy Image Recognition self-assessment will make you the established Image Recognition domain authority by revealing just what you need to know to be fluent and ready for any Image Recognition challenge. How do I reduce the effort in the Image Recognition work to be done to get problems solved? How can I ensure that plans of action include every Image Recognition task and that every Image Recognition outcome is in place? How will I save time investigating strategic and tactical options and ensuring Image Recognition costs are low? How can I deliver tailored Image Recognition advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Image Recognition essentials are covered, from every angle: the Image Recognition self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Image Recognition outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Image Recognition practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Image Recognition are maximized with professional results. Your purchase includes access details to the Image Recognition self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Image Recognition Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Download or read book Computer Vision and Action Recognition written by Md. Atiqur Rahman Ahad and published by Springer Science & Business Media. This book was released on 2011-12-02 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human action analyses and recognition are challenging problems due to large variations in human motion and appearance, camera viewpoint and environment settings. The field of action and activity representation and recognition is relatively old, yet not well-understood by the students and research community. Some important but common motion recognition problems are even now unsolved properly by the computer vision community. However, in the last decade, a number of good approaches are proposed and evaluated subsequently by many researchers. Among those methods, some methods get significant attention from many researchers in the computer vision field due to their better robustness and performance. This book will cover gap of information and materials on comprehensive outlook – through various strategies from the scratch to the state-of-the-art on computer vision regarding action recognition approaches. This book will target the students and researchers who have knowledge on image processing at a basic level and would like to explore more on this area and do research. The step by step methodologies will encourage one to move forward for a comprehensive knowledge on computer vision for recognizing various human actions.

Download or read book Handbook of Face Recognition written by Stan Z. Li and published by Springer Nature. This book was released on 2024-01-30 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: The history of computer-aided face recognition dates to the 1960s, yet the problem of automatic face recognition – a task that humans perform routinely and effortlessly in our daily lives – still poses great challenges, especially in unconstrained conditions. This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational recognition systems. After a thorough introduction, each subsequent chapter focuses on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Topics and features: Fully updated, revised, and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated detection and recognition systems Provides comprehensive coverage of face detection, alignment, feature extraction, and recognition technologies, and issues in evaluation, systems, security, and applications Contains numerous step-by-step algorithms Describes a broad range of applications from person verification, surveillance, and security, to entertainment Presents contributions from an international selection of preeminent experts Integrates numerous supporting graphs, tables, charts, and performance data This practical and authoritative reference is an essential resource for researchers, professionals and students involved in image processing, computer vision, biometrics, security, Internet, mobile devices, human-computer interface, E-services, computer graphics and animation, and the computer game industry.

Download or read book Handbook of Face Recognition written by Stan Z. Li and published by Springer Science & Business Media. This book was released on 2005-12-06 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the history of computer-aided face recognition stretches back to the 1960s, automatic face recognition remains an unsolved problem and still offers a great challenge to computer-vision and pattern recognition researchers. This handbook is a comprehensive account of face recognition research and technology, written by a group of leading international researchers. Twelve chapters cover all the sub-areas and major components for designing operational face recognition systems. Background, modern techniques, recent results, and challenges and future directions are considered. The book is aimed at practitioners and professionals planning to work in face recognition or wanting to become familiar with the state-of- the-art technology. A comprehensive handbook, by leading research authorities, on the concepts, methods, and algorithms for automated face detection and recognition. Essential reference resource for researchers and professionals in biometric security, computer vision, and video image analysis.

Download or read book Probabilistic Graphical Models written by Luis Enrique Sucar and published by Springer Nature. This book was released on 2020-12-23 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. It features new material on partially observable Markov decision processes, causal graphical models, causal discovery and deep learning, as well as an even greater number of exercises; it also incorporates a software library for several graphical models in Python. The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes. Topics and features: Presents a unified framework encompassing all of the main classes of PGMs Explores the fundamental aspects of representation, inference and learning for each technique Examines new material on partially observable Markov decision processes, and graphical models Includes a new chapter introducing deep neural networks and their relation with probabilistic graphical models Covers multidimensional Bayesian classifiers, relational graphical models, and causal models Provides substantial chapter-ending exercises, suggestions for further reading, and ideas for research or programming projects Describes classifiers such as Gaussian Naive Bayes, Circular Chain Classifiers, and Hierarchical Classifiers with Bayesian Networks Outlines the practical application of the different techniques Suggests possible course outlines for instructors This classroom-tested work is suitable as a textbook for an advanced undergraduate or a graduate course in probabilistic graphical models for students of computer science, engineering, and physics. Professionals wishing to apply probabilistic graphical models in their own field, or interested in the basis of these techniques, will also find the book to be an invaluable reference. Dr. Luis Enrique Sucar is a Senior Research Scientist at the National Institute for Astrophysics, Optics and Electronics (INAOE), Puebla, Mexico. He received the National Science Prize en 2016.

Download or read book Object Detection and Recognition in Digital Images written by Boguslaw Cyganek and published by John Wiley & Sons. This book was released on 2013-05-20 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields. Key features: Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications. Places an emphasis on tensor and statistical based approaches within object detection and recognition. Provides an overview of image clustering and classification methods which includes subspace and kernel based processing, mean shift and Kalman filter, neural networks, and k-means methods. Contains numerous case study examples of mainly automotive applications. Includes a companion website hosting full C++ implementation, of topics presented in the book as a software library, and an accompanying manual to the software platform.

Download or read book Deep Learning for Vision Systems written by Mohamed Elgendy and published by Manning Publications. This book was released on 2020-11-10 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. Summary Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can identify and react to objects in images, videos, and real life. With author Mohamed Elgendy's expert instruction and illustration of real-world projects, you’ll finally grok state-of-the-art deep learning techniques, so you can build, contribute to, and lead in the exciting realm of computer vision! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology How much has computer vision advanced? One ride in a Tesla is the only answer you’ll need. Deep learning techniques have led to exciting breakthroughs in facial recognition, interactive simulations, and medical imaging, but nothing beats seeing a car respond to real-world stimuli while speeding down the highway. About the book How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. What's inside Image classification and object detection Advanced deep learning architectures Transfer learning and generative adversarial networks DeepDream and neural style transfer Visual embeddings and image search About the reader For intermediate Python programmers. About the author Mohamed Elgendy is the VP of Engineering at Rakuten. A seasoned AI expert, he has previously built and managed AI products at Amazon and Twilio. Table of Contents PART 1 - DEEP LEARNING FOUNDATION 1 Welcome to computer vision 2 Deep learning and neural networks 3 Convolutional neural networks 4 Structuring DL projects and hyperparameter tuning PART 2 - IMAGE CLASSIFICATION AND DETECTION 5 Advanced CNN architectures 6 Transfer learning 7 Object detection with R-CNN, SSD, and YOLO PART 3 - GENERATIVE MODELS AND VISUAL EMBEDDINGS 8 Generative adversarial networks (GANs) 9 DeepDream and neural style transfer 10 Visual embeddings

Download or read book The Essential Guide to Image Processing written by Alan C. Bovik and published by Academic Press. This book was released on 2009-07-08 with total page 877 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete introduction to the basic and intermediate concepts of image processing from the leading people in the field Up-to-date content, including statistical modeling of natural, anistropic diffusion, image quality and the latest developments in JPEG 2000 This comprehensive and state-of-the art approach to image processing gives engineers and students a thorough introduction, and includes full coverage of key applications: image watermarking, fingerprint recognition, face recognition and iris recognition and medical imaging. "This book combines basic image processing techniques with some of the most advanced procedures. Introductory chapters dedicated to general principles are presented alongside detailed application-orientated ones. As a result it is suitably adapted for different classes of readers, ranging from Master to PhD students and beyond." – Prof. Jean-Philippe Thiran, EPFL, Lausanne, Switzerland "Al Bovik’s compendium proceeds systematically from fundamentals to today’s research frontiers. Professor Bovik, himself a highly respected leader in the field, has invited an all-star team of contributors. Students, researchers, and practitioners of image processing alike should benefit from the Essential Guide." – Prof. Bernd Girod, Stanford University, USA "This book is informative, easy to read with plenty of examples, and allows great flexibility in tailoring a course on image processing or analysis." – Prof. Pamela Cosman, University of California, San Diego, USA A complete and modern introduction to the basic and intermediate concepts of image processing – edited and written by the leading people in the field An essential reference for all types of engineers working on image processing applications Up-to-date content, including statistical modelling of natural, anisotropic diffusion, image quality and the latest developments in JPEG 2000

Download or read book Facial Recognition A Complete Guide written by Gerardus Blokdyk and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Facial Recognition A Complete Guide 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-01-28 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is different about mobile biometrics? What are you doing to protect your data from unauthorized access/use? Why digital customer centric transformation? How are the rules that govern tech designed? What is the False Accept Rate (FAR) of the biometric? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Facial Recognition investments work better. This Facial Recognition All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Facial Recognition Self-Assessment. Featuring 2201 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Facial Recognition improvements can be made. In using the questions you will be better able to: - diagnose Facial Recognition projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Facial Recognition and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Facial Recognition Scorecard, you will develop a clear picture of which Facial Recognition areas need attention. Your purchase includes access details to the Facial Recognition self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Facial Recognition Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Download or read book Image Processing written by Tinku Acharya and published by John Wiley & Sons. This book was released on 2005-10-03 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image processing-from basics to advanced applications Learn how to master image processing and compression with this outstanding state-of-the-art reference. From fundamentals to sophisticated applications, Image Processing: Principles and Applications covers multiple topics and provides a fresh perspective on future directions and innovations in the field, including: * Image transformation techniques, including wavelet transformation and developments * Image enhancement and restoration, including noise modeling and filtering * Segmentation schemes, and classification and recognition of objects * Texture and shape analysis techniques * Fuzzy set theoretical approaches in image processing, neural networks, etc. * Content-based image retrieval and image mining * Biomedical image analysis and interpretation, including biometric algorithms such as face recognition and signature verification * Remotely sensed images and their applications * Principles and applications of dynamic scene analysis and moving object detection and tracking * Fundamentals of image compression, including the JPEG standard and the new JPEG2000 standard Additional features include problems and solutions with each chapter to help you apply the theory and techniques, as well as bibliographies for researching specialized topics. With its extensive use of examples and illustrative figures, this is a superior title for students and practitioners in computer science, wireless and multimedia communications, and engineering.

Download or read book Practical Machine Learning for Computer Vision written by Valliappa Lakshmanan and published by "O'Reilly Media, Inc.". This book was released on 2021-07-21 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Fundamentals of Pattern Recognition and Machine Learning written by Ulisses Braga-Neto and published by Springer Nature. This book was released on 2020-09-10 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Pattern Recognition and Machine Learning is designed for a one or two-semester introductory course in Pattern Recognition or Machine Learning at the graduate or advanced undergraduate level. The book combines theory and practice and is suitable to the classroom and self-study. It has grown out of lecture notes and assignments that the author has developed while teaching classes on this topic for the past 13 years at Texas A&M University. The book is intended to be concise but thorough. It does not attempt an encyclopedic approach, but covers in significant detail the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as Gaussian process regression and convolutional neural networks. In addition, the selection of topics has a few features that are unique among comparable texts: it contains an extensive chapter on classifier error estimation, as well as sections on Bayesian classification, Bayesian error estimation, separate sampling, and rank-based classification. The book is mathematically rigorous and covers the classical theorems in the area. Nevertheless, an effort is made in the book to strike a balance between theory and practice. In particular, examples with datasets from applications in bioinformatics and materials informatics are used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and scikit-learn. All plots in the text were generated using python scripts, which are also available on the book website.

Download or read book Deep Learning Illustrated written by Jon Krohn and published by Addison-Wesley Professional. This book was released on 2019-08-05 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Download or read book Facial Recognition A Complete Guide 2019 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2019-07-03 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: What are the types and number of measures to use? How will you motivate the stakeholders with the least vested interest? What are your most important goals for the strategic facial recognition objectives? What are internal and external facial recognition relations? Has the facial recognition value of standards been quantified? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Facial Recognition investments work better. This Facial Recognition All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Facial Recognition Self-Assessment. Featuring 916 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Facial Recognition improvements can be made. In using the questions you will be better able to: - diagnose Facial Recognition projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Facial Recognition and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Facial Recognition Scorecard, you will develop a clear picture of which Facial Recognition areas need attention. Your purchase includes access details to the Facial Recognition self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Facial Recognition Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.