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Author : Lewis W. Tucker
Publisher :
ISBN 13 :
Total Pages : 6 pages
Book Rating : 4.:/5 (267 download)
Download or read book Model-based Object Recognition Using the Connection Machine written by Lewis W. Tucker and published by . This book was released on 1987 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Lewis W. Tucker
Publisher :
ISBN 13 :
Total Pages : 8 pages
Book Rating : 4.:/5 (265 download)
Download or read book Object Recognition Using the Connection Machine written by Lewis W. Tucker and published by . This book was released on 1988 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : John Winn
Publisher : CRC Press
ISBN 13 : 1498756824
Total Pages : 469 pages
Book Rating : 4.4/5 (987 download)
Download or read book Model-Based Machine Learning written by John Winn and published by CRC Press. This book was released on 2023-11-30 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains. A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to a concrete, real world problem. This book tackles this challenge through model-based machine learning which focuses on understanding the assumptions encoded in a machine learning system and their corresponding impact on the behaviour of the system. The key ideas of model-based machine learning are introduced through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications that it makes sense to discuss modelling assumptions. Each chapter introduces one case study and works through step-by-step to solve it using a model-based approach. The aim is not just to explain machine learning methods, but also showcase how to create, debug, and evolve them to solve a problem. Features: Explores the assumptions being made by machine learning systems and the effect these assumptions have when the system is applied to concrete problems. Explains machine learning concepts as they arise in real-world case studies. Shows how to diagnose, understand and address problems with machine learning systems. Full source code available, allowing models and results to be reproduced and explored. Includes optional deep-dive sections with more mathematical details on inference algorithms for the interested reader.
Author : Todd Anthony Cass
Publisher :
ISBN 13 :
Total Pages : 104 pages
Book Rating : 4.:/5 (249 download)
Download or read book Robust 2-D model-based object recognition written by Todd Anthony Cass and published by . This book was released on 1991 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: The results of simulations and experiments on real images based on a Connection Machine parallel supercomputer implementation are presented."
Author : S Poonkuntran
Publisher : CRC Press
ISBN 13 : 1000686795
Total Pages : 345 pages
Book Rating : 4.0/5 (6 download)
Download or read book Object Detection with Deep Learning Models written by S Poonkuntran and published by CRC Press. This book was released on 2022-11-01 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks. Features: A structured overview of deep learning in object detection A diversified collection of applications of object detection using deep neural networks Emphasize agriculture and remote sensing domains Exclusive discussion on moving object detection
Author : Daijin Kim
Publisher :
ISBN 13 :
Total Pages : 124 pages
Book Rating : 4.:/5 (731 download)
Download or read book Invariant Object Recognition Using Neural Network Ensemble on the Connection Machine written by Daijin Kim and published by . This book was released on 1991 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jean Ponce
Publisher : Springer
ISBN 13 : 3540687955
Total Pages : 622 pages
Book Rating : 4.5/5 (46 download)
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.
Author : Minsoo Suk
Publisher : Springer Science & Business Media
ISBN 13 : 4431682139
Total Pages : 318 pages
Book Rating : 4.4/5 (316 download)
Download or read book Three-Dimensional Object Recognition from Range Images written by Minsoo Suk and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Science Workbench is a monograph series which will provide you with an in-depth working knowledge of current developments in computer technology. Every volume in this series will deal with a topic of importance in computer science and elaborate on how you yourself can build systems related to the main theme. You will be able to develop a variety of systems, including computer software tools, computer graphics, computer animation, database management systems, and computer-aided design and manufacturing systems. Computer Science Workbench represents an important new contribution in the field of practical computer technology. T08iyasu L. Kunii PREFACE The primary aim of this book is to present a coherent and self-contained de scription of recent advances in three-dimensional object recognition from range images. Three-dimensional object recognition concerns recognition and localiza tion of objects of interest in a scene from input images. This problem is one of both theoretical and practical importance. On the theoretical side, it is an ideal vehicle for the study of the general area of computer vision since it deals with several important issues encountered in computer vision-for example, issues such as feature extraction, acquisition, representation and proper use of knowl edge, employment of efficient control strategies, coupling numerical and symbolic computations, and parallel implementation of algorithms. On the practical side, it has a wide range of applications in areas such as robot vision, autonomous navigation, automated inspection of industrial parts, and automated assembly.
Author : Massachusetts Institute of Technology. Artificial Intelligence Laboratory
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (271 download)
Download or read book Robust 2-D Model-based Object Recognition written by Massachusetts Institute of Technology. Artificial Intelligence Laboratory and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Techniques, suitable for parallel implementation, for robust 2D model-based object recognition in the presence of sensor error are studied. Models and scene data are represented as local geometric features and robust hypothesis of feature matchings and transformations is considered. Bounds on the error in the image feature geometry are assumed constraining possible matchings and transformations. {\it Transformation sampling} is introduced as a simple, robust, polynomial-time, and highly parallel method of searching the space of transformations to hypothesize feature matchings. Key to the approach is that error in image feature measurement is explicitly accounted for. A Connection Machine implementation and experiments on real images are presented.
Author :
Publisher : Springer
ISBN 13 : 9780387307718
Total Pages : 0 pages
Book Rating : 4.3/5 (77 download)
Download or read book Computer Vision written by and published by Springer. This book was released on 2014-04-22 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive reference provides easy access to relevant information on all aspects of Computer Vision. An A-Z format of over 240 entries offers a diverse range of topics for those seeking entry into any aspect within the broad field of Computer Vision. Over 200 Authors from both industry and academia contributed to this volume. Each entry includes synonyms, a definition and discussion of the topic, and a robust bibliography. Extensive cross-references to other entries support efficient, user-friendly searches for immediate access to relevant information. Entries were peer-reviewed by a distinguished international advisory board, both scientifically and geographically diverse, ensuring balanced coverage. Over 3700 bibliographic references for further reading enable deeper exploration into any of the topics covered. The content of Computer Vision: A Reference Guide is expository and tutorial, making the book a practical resource for students who are considering entering the field, as well as professionals in other fields who need to access this vital information but may not have the time to work their way through an entire text on their topic of interest.
Author : United States. Defense Advanced Research Projects Agency. Information Science and Technology Office
Publisher :
ISBN 13 :
Total Pages : 440 pages
Book Rating : 4.3/5 (91 download)
Download or read book Image Understanding Workshop written by United States. Defense Advanced Research Projects Agency. Information Science and Technology Office and published by . This book was released on 1987 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Louise Stark
Publisher : World Scientific
ISBN 13 : 9789810215088
Total Pages : 162 pages
Book Rating : 4.2/5 (15 download)
Download or read book Generic Object Recognition Using Form & Function written by Louise Stark and published by World Scientific. This book was released on 1996 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides a detailed record of the ?GRUFF? research project. The goal of the GRUFF project is to develop techniques for robotic vision systems to recognize objects by reasoning about their intended function rather than matching to a pre-defined database of 2-D object appearances or 3-D object shapes. The contributions of this work are: a demonstration of the feasibility of the ?form and function? approach to reasoning about 3-D shapes; a demonstration of the concept of using a small number of knowledge primitives as component building blocks in creating a function-based definition of an object category; and an indexing mechanism to make processing for recognition more efficient without any substantial decrease in correctness of classification. Results are given for the analysis of over 500 3-D shape descriptions created with a solid modeling tool and over 200 shape descriptions extracted from real laser range finder images.
Author :
Publisher :
ISBN 13 :
Total Pages : 688 pages
Book Rating : 4.:/5 (318 download)
Download or read book Image Understanding Workshop written by and published by . This book was released on 1988 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jason Brownlee
Publisher : Machine Learning Mastery
ISBN 13 :
Total Pages : 564 pages
Book Rating : 4./5 ( download)
Download or read book Deep Learning for Computer Vision written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2019-04-04 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.
Author : 黃業新
Publisher : Open Dissertation Press
ISBN 13 : 9781361412046
Total Pages : pages
Book Rating : 4.4/5 (12 download)
Download or read book A Two-Level Model-Based Object Recognition Technique written by 黃業新 and published by Open Dissertation Press. This book was released on 2017-01-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "A Two-level Model-based Object Recognition Technique" by 黃業新, Yip-san, Wong, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b3121380 Subjects: Pattern recognition systems Computer vision
Author : Roohie Naaz Mir
Publisher : CRC Press
ISBN 13 : 1000880419
Total Pages : 319 pages
Book Rating : 4.0/5 (8 download)
Download or read book Advancement of Deep Learning and its Applications in Object Detection and Recognition written by Roohie Naaz Mir and published by CRC Press. This book was released on 2023-05-10 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Object detection is a basic visual identification problem in computer vision that has been explored extensively over the years. Visual object detection seeks to discover objects of specific target classes in a given image with pinpoint accuracy and apply a class label to each object instance. Object recognition strategies based on deep learning have been intensively investigated in recent years as a result of the remarkable success of deep learning-based image categorization. In this book, we go through in detail detector architectures, feature learning, proposal generation, sampling strategies, and other issues that affect detection performance. The book describes every newly proposed novel solution but skips through the fundamentals so that readers can see the field's cutting edge more rapidly. Moreover, unlike prior object detection publications, this project analyses deep learning-based object identification methods systematically and exhaustively, and also gives the most recent detection solutions and a collection of noteworthy research trends. The book focuses primarily on step-by-step discussion, an extensive literature review, detailed analysis and discussion, and rigorous experimentation results. Furthermore, a practical approach is displayed and encouraged.
Author : Marco Alexander Treiber
Publisher : Springer
ISBN 13 : 9781849962360
Total Pages : 202 pages
Book Rating : 4.9/5 (623 download)
Download or read book An Introduction to Object Recognition written by Marco Alexander Treiber and published by Springer. This book was released on 2013-01-02 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid development of computer hardware has enabled usage of automatic object recognition in an increasing number of applications, ranging from industrial image processing to medical applications, as well as tasks triggered by the widespread use of the internet. Each area of application has its specific requirements, and consequently these cannot all be tackled appropriately by a single, general-purpose algorithm. This easy-to-read text/reference provides a comprehensive introduction to the field of object recognition (OR). The book presents an overview of the diverse applications for OR and highlights important algorithm classes, presenting representative example algorithms for each class. The presentation of each algorithm describes the basic algorithm flow in detail, complete with graphical illustrations. Pseudocode implementations are also included for many of the methods, and definitions are supplied for terms which may be unfamiliar to the novice reader. Supporting a clear and intuitive tutorial style, the usage of mathematics is kept to a minimum. Topics and features: presents example algorithms covering global approaches, transformation-search-based methods, geometrical model driven methods, 3D object recognition schemes, flexible contour fitting algorithms, and descriptor-based methods; explores each method in its entirety, rather than focusing on individual steps in isolation, with a detailed description of the flow of each algorithm, including graphical illustrations; explains the important concepts at length in a simple-to-understand style, with a minimum usage of mathematics; discusses a broad spectrum of applications, including some examples from commercial products; contains appendices discussing topics related to OR and widely used in the algorithms, (but not at the core of the methods described in the chapters). Practitioners of industrial image processing will find this simple introduction and overview to OR a valuable reference, as will graduate students in computer vision courses. Marco Treiber is a software developer at Siemens Electronics Assembly Systems, Munich, Germany, where he is Technical Lead in Image Processing for the Vision System of SiPlace placement machines, used in SMT assembly.
