Medial Measures For Recognition Mapping And Categorization
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Medial Measures For Recognition Mapping And Categorization
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Author : Morteza Rezanejad
language : en
Publisher: McGill University
Release Date :
Medial Measures For Recognition Mapping And Categorization written by Morteza Rezanejad and has been published by McGill University this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Visual shape analysis plays a fundamental role in perception by man and by computer, allowing for inferences about properties of objects and scenes in the physical world. Mathematical approaches to describing visual form can benefit from the use of representations that simultaneously capture properties of an object's outline as well as its interior. Motivated by the success of medial models, this doctoral thesis revisits a quantity related to medial axis computations, the average outward flux of the gradient of the Euclidean distance function from a boundary, and then addresses three distinct problems using this measure. First, I consider the problem of view sphere partitioning for view-based object recognition from sparse views. View-based 3D object recognition requires a selection of model object views against which to match a query view. Ideally, for this to be computationally efficient, such a selection should be sparse. To address this problem, I introduce a novel hierarchical partitioning of the view sphere into regions within which the silhouette of a model object is qualitatively unchanged. To achieve this, I propose a part-based abstraction of a skeleton, as a graph, dubbed the Flux Graph, which allows for views to be grouped. Next, I consider the problem of mapping an initially-unknown 2D environment from possibly noisy sensed samples via an on-line procedure which robustly computes a retraction of its boundaries to obtain a topological representation. Here I motto an algorithm that allows for online map construction with loop closure. I demonstrate that the proposed method allows the robot to localize itself on a partially constructed map to calculate a path to unexplored parts of the environment (frontiers), to compute a robust terminating condition when the robot has fully explored the environment, and finally to achieve loop closure detection. I also show that the resulting map is stable under disturbances to the sensed boundary, and to variations in starting locations for exploration. Finally, I consider the problem of scene categorization from complex line drawings. In the context of human vision, we show that local ribbon symmetry between neighboring pairs of contours facilitates the categorization of complex real-world environments by human observers. In the context of computer vision, I demonstrate a high level of performance in the problem of convolutional neural network-based recognition of natural scenes from line drawings, even in the absence of color, texture and shading information.
Medial Measures For Recognition Mapping And Categorization
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Author : Morteza Rezanejad
language : en
Publisher:
Release Date : 2020
Medial Measures For Recognition Mapping And Categorization written by Morteza Rezanejad and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
"Visual shape analysis plays a fundamental role in perception by man and by computer, allowing for inferences about properties of objects and scenes in the physical world. Mathematical approaches to describing visual form can benefit from the use of representations that simultaneously capture properties of an object's outline as well as its interior. Motivated by the success of medial models, this doctoral thesis revisits a quantity related to medial axis computations, the average outward flux of the gradient of the Euclidean distance function from a boundary, and then addresses three distinct problems using this measure. First, I consider the problem of view sphere partitioning for view-based object recognition from sparse views. View-based 3D object recognition requires a selection of model object views against which to match a query view. Ideally, for this to be computationally efficient, such a selection should be sparse. To address this problem, I introduce a novel hierarchical partitioning of the view sphere into regions within which the silhouette of a model object is qualitatively unchanged. To achieve this, I propose a part-based abstraction of a skeleton, as a graph, dubbed the Flux Graph, which allows for views to be grouped. Next, I consider the problem of mapping an initially-unknown 2D environment from possibly noisy sensed samples via an on-line procedure which robustly computes a retraction of its boundaries to obtain a topological representation. Here I devise an algorithm that allows for online map construction with loop closure. I demonstrate that the proposed method allows the robot to localize itself on a partially constructed map to calculate a path to unexplored parts of the environment (frontiers), to compute a robust terminating condition when the robot has fully explored the environment, and finally to achieve loop closure detection. I also show that the resulting map is stable under perturbations to the sensed boundary, and to variations in starting locations for exploration. Finally, I consider the problem of scene categorization from complex line drawings. In the context of human vision, we show that local ribbon symmetry between neighboring pairs of contours facilitates the categorization of complex real-world environments by human observers. In the context of computer vision, I demonstrate a high level of performance in the problem of convolutional neural network-based recognition of natural scenes from line drawings, even in the absence of color, texture and shading information. I then show that the inclusion of medial-axis based contour salience weights leads to a further boost in recognition performance, adding useful information that does not appear to be exploited when the neural networks are trained on contours alone"--
Modern Computational Intelligence Methods For The Interpretation Of Medical Images
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Author : Ryszard Tadeusiewicz
language : en
Publisher: Springer
Release Date : 2008-01-12
Modern Computational Intelligence Methods For The Interpretation Of Medical Images written by Ryszard Tadeusiewicz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-12 with Medical categories.
A detailed description of up-to-date methods used for computer processing and interpretation of medical images is given. The scope of the book include images acquisition, storing with compression, processing, analysis, recognition and also its automatic understanding In introduction general overview of the computer vision methods designed for medical images is presented. Next sources of medical images are presented with their general characteristics. Both traditional (like X-ray) and very modern (like PET) sources of medical images are presented. The main emphasis is placed on such properties of medical images given by particular medical imaging methods which are important form the point of view of its computer processing, analysis and recognition. The consecutive parts of the book describe compression and processing methods, including many methods developed by authors especially for medical images. After parts describing analysis and recognition of medical images come most important part, in which the new method of automatic understanding of medical images is given. This new method of image interpretation, described in previous works of the same authors with applications for simple 2D images now is generalized for 3D images and for complex medical images with many objects observed and with complicated relations between these objects.
Progress In Medical Imaging
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Author : Vernon L. Newhouse
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Progress In Medical Imaging written by Vernon L. Newhouse and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Medical categories.
Progress in Medical Imaging contains a collection of interdisciplinary reviews of subtopics in medical imaging written by internationally known experts. Topics contained in the book include automatic recognition of cells and tissue types in light microscopy, computerized manipulation and assembly of two-dimensional scans of an organ into images of the three-dimensional organ which can be rotated in space, techniques for reducing the image degradation produced by scattering radiation in chest radiography, recent advances in instrumentation, and principles of positron-emission tomography. The final chapters of this book describe the advantages of pseudo-random codes as transmitted signals for ultrasonic flow measurement, imaging, and medium characterization. The primary audience for Progress in Medical Imaging includes engineers, physicists, and students engaged in research, development, or applications of medical imaging.
Decision Processes In Dynamic Probabilistic Systems
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Author : A.V. Gheorghe
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Decision Processes In Dynamic Probabilistic Systems written by A.V. Gheorghe and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
'Et moi - ... - si j'avait su comment en revenir. One service mathematics has rendered the je n'y serais point aile: human race. It has put common sense back where it belongs. on the topmost shelf next Jules Verne (0 the dusty canister labelled 'discarded non sense'. The series is divergent; therefore we may be able to do something with it. Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic has rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
Computational Maps In The Visual Cortex
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Author : Risto Miikkulainen
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-08-09
Computational Maps In The Visual Cortex written by Risto Miikkulainen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-08-09 with Science categories.
For more than 30 years, the visual cortex has been the source of new theories and ideas about how the brain processes information. The visual cortex is easily accessible through a variety of recording and imagining techniques and allows mapping of high level behavior relatively directly to neural mechanisms. Understanding the computations in the visual cortex is therefore an important step toward a general theory of computational brain theory.
World Congress On Neural Networks San Diego
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Author :
language : en
Publisher: Psychology Press
Release Date : 1994
World Congress On Neural Networks San Diego written by and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Artificial intelligence categories.
World Congress On Neural Networks
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Author : Paul Werbos
language : en
Publisher: Routledge
Release Date : 2021-09-10
World Congress On Neural Networks written by Paul Werbos and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-10 with Psychology categories.
Centered around 20 major topic areas of both theoretical and practical importance, the World Congress on Neural Networks provides its registrants -- from a diverse background encompassing industry, academia, and government -- with the latest research and applications in the neural network field.
Fuzzy Cognitive Maps
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Author : Philippe J. Giabbanelli
language : en
Publisher: Springer Nature
Release Date : 2024-01-29
Fuzzy Cognitive Maps written by Philippe J. Giabbanelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-29 with Mathematics categories.
This book starts with the rationale for creating an FCM by contrast to other techniques for participatory modeling, as this rationale is a key element to justify the adoption of techniques in a research paper. Fuzzy cognitive mapping is an active research field with over 20,000 publications devoted to externalizing the qualitative perspectives or “mental models” of individuals and groups. Since the emergence of fuzzy cognitive maps (FCMs) back in the 80s, new algorithms have been developed to reduce bias, facilitate the externalization process, or efficiently utilize quantitative data via machine learning. It covers the development of an FCM with participants through a traditional in-person setting, drawing from the experience of practitioners and highlighting solutions to commonly encountered challenges. The book continues with introducing principles of simulations with FCMs as a tool to perform what-if scenario analysis, while extending those principles to more elaborated simulation scenarios where FCMs and agent-based modeling are combined. Once an FCM model is obtained, the book then details the analytical tools available for practitioners (e.g., to identify the most important factors) and provides examples to aid in the interpretation of results. The discussion concerning relevant extensions is equally pertinent, which are devoted to increasing the expressiveness of the FCM formalism in problems involving uncertainty. The last four chapters focus on building FCM models from historical data. These models are typically needed when facing multi-output prediction or pattern classification problems. In that regard, the book smoothly guides the reader from simple approaches to more elaborated algorithms, symbolizing the noticeable progress of this field in the last 35 years. Problems, recent references, and functional codes are included in each chapter to provide practice and support further learning from practitioners and researchers.
Pattern Classification Of Medical Images Computer Aided Diagnosis
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Author : Xiao-Xia Yin
language : en
Publisher: Springer
Release Date : 2017-06-27
Pattern Classification Of Medical Images Computer Aided Diagnosis written by Xiao-Xia Yin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-27 with Computers categories.
This book presents advances in biomedical imaging analysis and processing techniques using time dependent medical image datasets for computer aided diagnosis. The analysis of time-series images is one of the most widely appearing problems in science, engineering, and business. In recent years this problem has gained importance due to the increasing availability of more sensitive sensors in science and engineering and due to the wide-spread use of computers in corporations which have increased the amount of time-series data collected by many magnitudes. An important feature of this book is the exploration of different approaches to handle and identify time dependent biomedical images. Biomedical imaging analysis and processing techniques deal with the interaction between all forms of radiation and biological molecules, cells or tissues, to visualize small particles and opaque objects, and to achieve the recognition of biomedical patterns. These are topics of great importance to biomedical science, biology, and medicine. Biomedical imaging analysis techniques can be applied in many different areas to solve existing problems. The various requirements arising from the process of resolving practical problems motivate and expedite the development of biomedical imaging analysis. This is a major reason for the fast growth of the discipline.