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Inverse Scale Invariant Feature Transform Models For Object Recognition And Image Tagging
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Book Synopsis Visual Object Recognition by : Kristen Grauman
Download or read book Visual Object Recognition written by Kristen Grauman and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: Specific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions
Book Synopsis Practical Deep Learning for Cloud, Mobile, and Edge by : Anirudh Koul
Download or read book Practical Deep Learning for Cloud, Mobile, and Edge written by Anirudh Koul and published by "O'Reilly Media, Inc.". This book was released on 2019-10-14 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users
Book Synopsis Representations and Techniques for 3D Object Recognition and Scene Interpretation by : Derek Hoiem
Download or read book Representations and Techniques for 3D Object Recognition and Scene Interpretation written by Derek Hoiem and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions
Book Synopsis Surface Models for Geosciences by : Kateřina Růžičková
Download or read book Surface Models for Geosciences written by Kateřina Růžičková and published by Springer. This book was released on 2015-05-27 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of the conference is to present and discuss new methods, issues and challenges encountered in all parts of the complex process of gradual development and application of digital surface models. This process covers data capture, data generation, storage, model creation, validation, manipulation, utilization and visualization. Each stage requires suitable methods and involves issues that may substantially decrease the value of the model. Furthermore, the conference provides a platform to discuss the requirements, features and research approaches for 3D modeling, continuous field modeling and other geoscience applications. The conference covers the following topics: - LIDAR for elevation data - Radar interferometry for elevation data - Surface model creation - Surface model statistics - Surface model storage (including data formats, standardization, database) - Feature extraction - Analysis of surface models - Surface models for hydrology, meteorology, climatology - Surface models for signal spreading - Surface models for geology (structural, mining) - Surface models for environmental science - Surface models for visibility studies - Surface models for urban geography - Surface models for human geography - Uncertainty of surface models and digital terrain analysis - Surface model visual enhancement and rendering
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.
Book Synopsis Local Invariant Feature Detectors by : Tinne Tuytelaars
Download or read book Local Invariant Feature Detectors written by Tinne Tuytelaars and published by Now Publishers Inc. This book was released on 2008 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: Local Invariant Features Detectors is an overview of invariant interest point detectors, how they evolved over time, how they work, and what their respective strengths and weaknesses are.
Book Synopsis Template Matching Techniques in Computer Vision by : Roberto Brunelli
Download or read book Template Matching Techniques in Computer Vision written by Roberto Brunelli and published by John Wiley & Sons. This book was released on 2009-04-29 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli: examines the basics of digital image formation, highlighting points critical to the task of template matching; presents basic and advanced template matching techniques, targeting grey-level images, shapes and point sets; discusses recent pattern classification paradigms from a template matching perspective; illustrates the development of a real face recognition system; explores the use of advanced computer graphics techniques in the development of computer vision algorithms. Template Matching Techniques in Computer Vision is primarily aimed at practitioners working on the development of systems for effective object recognition such as biometrics, robot navigation, multimedia retrieval and landmark detection. It is also of interest to graduate students undertaking studies in these areas.
Book Synopsis Handbook of Forensic Photography by : Sanford Weiss
Download or read book Handbook of Forensic Photography written by Sanford Weiss and published by CRC Press. This book was released on 2022-06-20 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Forensic Photography is the most-comprehensive, definitive reference for the use of photography in the capture and presentation of forensic evidence. The intent is to inform the reader about the most complete and up-to-date methods to capture and reproduce images that most accurately represent the evidence. With the rise in importance of forensic science, crime and accident scene documentation has likewise increased in importance—not the least of which has been forensic photography. The need to use accepted practice and protocols to guarantee the authenticity of images for evidence documentation is paramount for using it in court. And as with any discipline, there is an art to the science of forensic photography. Contributing authors from various backgrounds—each experts in their field—have provided numerous case examples, best practices, and recommendations for recognizing, recording, and preserving evidence using cameras and the latest digital image technology, including video and other imaging technologies. Chapters present such topics as videography, drone photography, underwater photography, crime scene photography, autopsy photographs, fire documentation, forensic odontology, and more. The book closes with coverage of courtroom displays, presenting imaging evidence and expert witness testimony in the courtroom. Handbook of Forensic Photography is a must-have reference for experienced crime scene photographers, death and crime scene investigators, police, and forensic professionals—including medical examiners, odontologists, engineers, and forensic anthropologists—who frequently need to capture investigative photographs in the course of investigations.
Book Synopsis Advances in Neural Information Processing Systems 11 by : Michael S. Kearns
Download or read book Advances in Neural Information Processing Systems 11 written by Michael S. Kearns and published by MIT Press. This book was released on 1999 with total page 1122 pages. Available in PDF, EPUB and Kindle. Book excerpt: The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.
Author :Xiaogang Wang Publisher :Foundations and Trends (R) in Signal Processing ISBN 13 :9781680831160 Total Pages :186 pages Book Rating :4.8/5 (311 download)
Book Synopsis Deep Learning in Object Recognition, Detection, and Segmentation by : Xiaogang Wang
Download or read book Deep Learning in Object Recognition, Detection, and Segmentation written by Xiaogang Wang and published by Foundations and Trends (R) in Signal Processing. This book was released on 2016-07-14 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning in Object Recognition, Detection, and Segmentation provides a comprehensive introductory overview of a topic that is having major impact on many areas of research in signal processing, computer vision, and machine learning.
Book Synopsis Handbook Of Pattern Recognition And Computer Vision (2nd Edition) by : Chi Hau Chen
Download or read book Handbook Of Pattern Recognition And Computer Vision (2nd Edition) written by Chi Hau Chen and published by World Scientific. This book was released on 1999-03-12 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.
Book Synopsis Algorithms for Image Processing and Computer Vision by : J. R. Parker
Download or read book Algorithms for Image Processing and Computer Vision written by J. R. Parker and published by John Wiley & Sons. This book was released on 2010-11-29 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It’s an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists who require highly specialized image processing. Algorithms now exist for a wide variety of sophisticated image processing applications required by software engineers and developers, advanced programmers, graphics programmers, scientists, and related specialists This bestselling book has been completely updated to include the latest algorithms, including 2D vision methods in content-based searches, details on modern classifier methods, and graphics cards used as image processing computational aids Saves hours of mathematical calculating by using distributed processing and GPU programming, and gives non-mathematicians the shortcuts needed to program relatively sophisticated applications. Algorithms for Image Processing and Computer Vision, 2nd Edition provides the tools to speed development of image processing applications.
Book Synopsis Interpretable Machine Learning by : Christoph Molnar
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Book Synopsis Sparse Modeling for Image and Vision Processing by : Julien Mairal
Download or read book Sparse Modeling for Image and Vision Processing written by Julien Mairal and published by Now Publishers. This book was released on 2014-12-19 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sparse Modeling for Image and Vision Processing offers a self-contained view of sparse modeling for visual recognition and image processing. More specifically, it focuses on applications where the dictionary is learned and adapted to data, yielding a compact representation that has been successful in various contexts.
Book Synopsis Deep Learning and Convolutional Neural Networks for Medical Image Computing by : Le Lu
Download or read book Deep Learning and Convolutional Neural Networks for Medical Image Computing written by Le Lu and published by Springer. This book was released on 2017-07-12 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
Book Synopsis Object Recognition by : M. Bennamoun
Download or read book Object Recognition written by M. Bennamoun and published by Springer Science & Business Media. This book was released on 2001-12-12 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.
Book Synopsis Toward Category-Level Object Recognition by : Jean Ponce
Download or read book Toward Category-Level Object Recognition written by Jean Ponce and published by Springer. This book was released on 2007-01-25 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 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.
