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Medial Measures For Recognition Mapping And Categorization
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Book Synopsis Medial measures for recognition, mapping and categorization by : Morteza Rezanejad
Download or read book Medial measures for recognition, mapping and categorization written by Morteza Rezanejad and published by McGill University. This book was released on with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Medical Image Recognition, Segmentation and Parsing by : S. Kevin Zhou
Download or read book Medical Image Recognition, Segmentation and Parsing written by S. Kevin Zhou and published by Academic Press. This book was released on 2015-12-11 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: - Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects - Methods and theories for medical image recognition, segmentation and parsing of multiple objects - Efficient and effective machine learning solutions based on big datasets - Selected applications of medical image parsing using proven algorithms - Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects - Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets - Includes algorithms for recognizing and parsing of known anatomies for practical applications
Book Synopsis Pattern Classification of Medical Images: Computer Aided Diagnosis by : Xiao-Xia Yin
Download or read book Pattern Classification of Medical Images: Computer Aided Diagnosis written by Xiao-Xia Yin and published by Springer. This book was released on 2017-06-27 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Artificial Intelligence in Recognition and Classification of Astrophysical and Medical Images by : Valentina Zharkova
Download or read book Artificial Intelligence in Recognition and Classification of Astrophysical and Medical Images written by Valentina Zharkova and published by Springer Science & Business Media. This book was released on 2007-03-07 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents innovative techniques in recognition and classification of astrophysical and medical images. Coverage includes: image standardization and enhancement; region-based methods for pattern recognition in medical and astrophysical images; advanced information processing using statistical methods; and feature recognition and classification using spectral method.
Book Synopsis Speaker Classification I by : Christian Müller
Download or read book Speaker Classification I written by Christian Müller and published by Springer Science & Business Media. This book was released on 2007-08-14 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume and its companion volume LNAI 4441 constitute a state-of-the-art survey in the field of speaker classification. Together they address such intriguing issues as how speaker characteristics are manifested in voice and speaking behavior. The nineteen contributions in this volume are organized into topical sections covering fundamentals, characteristics, applications, methods, and evaluation.
Book Synopsis Deep Network Design for Medical Image Computing by : Haofu Liao
Download or read book Deep Network Design for Medical Image Computing written by Haofu Liao and published by Academic Press. This book was released on 2022-08-24 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Network Design for Medical Image Computing: Principles and Applications covers a range of MIC tasks and discusses design principles of these tasks for deep learning approaches in medicine. These include skin disease classification, vertebrae identification and localization, cardiac ultrasound image segmentation, 2D/3D medical image registration for intervention, metal artifact reduction, sparse-view artifact reduction, etc. For each topic, the book provides a deep learning-based solution that takes into account the medical or biological aspect of the problem and how the solution addresses a variety of important questions surrounding architecture, the design of deep learning techniques, when to introduce adversarial learning, and more. This book will help graduate students and researchers develop a better understanding of the deep learning design principles for MIC and to apply them to their medical problems. - Explains design principles of deep learning techniques for MIC - Contains cutting-edge deep learning research on MIC - Covers a broad range of MIC tasks, including the classification, detection, segmentation, registration, reconstruction and synthesis of medical images
Book Synopsis Data Modeling for Metrology and Testing in Measurement Science by : Franco Pavese
Download or read book Data Modeling for Metrology and Testing in Measurement Science written by Franco Pavese and published by Springer Science & Business Media. This book was released on 2008-12-16 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provide a comprehensive set of modeling methods for data and uncertainty analysis, taking readers beyond mainstream methods and focusing on techniques with a broad range of real-world applications. The book will be useful as a textbook for graduate students, or as a training manual in the fields of calibration and testing. The work may also serve as a reference for metrologists, mathematicians, statisticians, software engineers, chemists, and other practitioners with a general interest in measurement science.
Author :Sanghamitra Bandyopadhyay Publisher :Springer Science & Business Media ISBN 13 :3540496076 Total Pages :320 pages Book Rating :4.5/5 (44 download)
Book Synopsis Classification and Learning Using Genetic Algorithms by : Sanghamitra Bandyopadhyay
Download or read book Classification and Learning Using Genetic Algorithms written by Sanghamitra Bandyopadhyay and published by Springer Science & Business Media. This book was released on 2007-05-17 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It examines how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries. Coverage also demonstrates the effectiveness of the genetic classifiers vis-à-vis several widely used classifiers, including neural networks.
Book Synopsis Self-Organizing Maps by : Teuvo Kohonen
Download or read book Self-Organizing Maps written by Teuvo Kohonen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second, revised edition of this book was suggested by the impressive sales of the first edition. Fortunately this enabled us to incorporate new important results that had just been obtained. The ASSOM (Adaptive-Subspace SOM) is a new architecture in which invariant-feature detectors emerge in an unsupervised learning process. Its basic principle was already introduced in the first edition, but the motiva tion and theoretical discussion in the second edition is more thorough and consequent. New material has been added to Sect. 5.9 and this section has been rewritten totally. Correspondingly, Sect. 1.4, which deals with adaptive subspace classifiers in general and constitutes the prerequisite for the ASSOM principle, has also been extended and rewritten totally. Another new SOM development is the WEBSOM, a two-layer architecture intended for the organization of very large collections of full-text documents such as those found in the Internet and World Wide Web. This architecture was published after the first edition came out. The idea and results seemed to be so important that the new Sect. 7.8 has now been added to the second edition. Another addition that contains new results is Sect. 3.15, which describes the acceleration in the computing of very large SOMs. It was also felt that Chap. 7, which deals with 80M applications, had to be extended.
Book Synopsis Real-Time Object Measurement and Classification by : Anil K. Jain
Download or read book Real-Time Object Measurement and Classification written by Anil K. Jain and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains papers presented at the NATO Advanced Research Workshop on "Real-time Object and Environment Measurement and Classification" held in Hotel Villa del Mare, Maratea, Italy, August 31 - September 3, 1987. This workshop was organized under the NATO Special Programme on Sensory Systems for Robotic Control. Professor Eric Backer, Delft University of Technology, The Netherlands and Professor Erdal Panayirci, Technical University of Istanbul, Turkey were the members of the organizing committee for this workshop. There were four major themes of this workshop: Real-time Requirements, Feature Measurement, Object Representation and Recognition, and Architecture for Measurement and Classification. A total of twenty-five technical presentations were made. These talks covered a wide spectrum of topics including hardware implementation of specific vision algorithms, a complete vision system for object tracking and inspection, using three cameras (trinocular stereo) for feature measurement, neural network for object recognition, integration of CAD (Computer-Aided Design) and vision systems, and the use of pyramid architectures for solving varioos computer vision problems.
Book Synopsis Neural Information Processing by : Tingwen Huang
Download or read book Neural Information Processing written by Tingwen Huang and published by Springer. This book was released on 2012-11-05 with total page 775 pages. Available in PDF, EPUB and Kindle. Book excerpt: The five volume set LNCS 7663, LNCS 7664, LNCS 7665, LNCS 7666 and LNCS 7667 constitutes the proceedings of the 19th International Conference on Neural Information Processing, ICONIP 2012, held in Doha, Qatar, in November 2012. The 423 regular session papers presented were carefully reviewed and selected from numerous submissions. These papers cover all major topics of theoretical research, empirical study and applications of neural information processing research. The 5 volumes represent 5 topical sections containing articles on theoretical analysis, neural modeling, algorithms, applications, as well as simulation and synthesis.
Author :Sanghamitra Bandyopadhyay Publisher :Springer Science & Business Media ISBN 13 :3642324517 Total Pages :271 pages Book Rating :4.6/5 (423 download)
Book Synopsis Unsupervised Classification by : Sanghamitra Bandyopadhyay
Download or read book Unsupervised Classification written by Sanghamitra Bandyopadhyay and published by Springer Science & Business Media. This book was released on 2012-12-13 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clustering is an important unsupervised classification technique where data points are grouped such that points that are similar in some sense belong to the same cluster. Cluster analysis is a complex problem as a variety of similarity and dissimilarity measures exist in the literature. This is the first book focused on clustering with a particular emphasis on symmetry-based measures of similarity and metaheuristic approaches. The aim is to find a suitable grouping of the input data set so that some criteria are optimized, and using this the authors frame the clustering problem as an optimization one where the objectives to be optimized may represent different characteristics such as compactness, symmetrical compactness, separation between clusters, or connectivity within a cluster. They explain the techniques in detail and outline many detailed applications in data mining, remote sensing and brain imaging, gene expression data analysis, and face detection. The book will be useful to graduate students and researchers in computer science, electrical engineering, system science, and information technology, both as a text and as a reference book. It will also be useful to researchers and practitioners in industry working on pattern recognition, data mining, soft computing, metaheuristics, bioinformatics, remote sensing, and brain imaging.
Book Synopsis Neuro-Fuzzy and Fuzzy-Neural Applications in Telecommunications by : Peter Stavroulakis
Download or read book Neuro-Fuzzy and Fuzzy-Neural Applications in Telecommunications written by Peter Stavroulakis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the first time, this highly interdisciplinary book covers the applications of neuro-fuzzy and fuzzy-neural scientific tools in a very wide area within the communications field. It deals with the important and modern areas of telecommunications amenable to such a treatment.
Book Synopsis Combatting Cyberbullying in Digital Media with Artificial Intelligence by : Mohamed Lahby
Download or read book Combatting Cyberbullying in Digital Media with Artificial Intelligence written by Mohamed Lahby and published by CRC Press. This book was released on 2023-12-13 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid advancements in mobile computing and communication technology and recent technological progress have opened up a plethora of opportunities. These advancements have expanded knowledge, facilitated global business, enhanced collaboration, and connected people through various digital media platforms. While these virtual platforms have provided new avenues for communication and self-expression, they also pose significant threats to our privacy. As a result, we must remain vigilant against the propagation of electronic violence through social networks. Cyberbullying has emerged as a particularly concerning form of online harassment and bullying, with instances of racism, terrorism, and various types of trolling becoming increasingly prevalent worldwide. Addressing the issue of cyberbullying to find effective solutions is a challenge for the web mining community, particularly within the realm of social media. In this context, artificial intelligence (AI) can serve as a valuable tool in combating the diverse manifestations of cyberbullying on the Internet and social networks. This book presents the latest cutting-edge research, theoretical methods, and novel applications in AI techniques to combat cyberbullying. Discussing new models, practical solutions, and technological advances related to detecting and analyzing cyberbullying is based on AI models and other related techniques. Furthermore, the book helps readers understand AI techniques to combat cyberbullying systematically and forthrightly, as well as future insights and the societal and technical aspects of natural language processing (NLP)-based cyberbullying research efforts. Key Features: Proposes new models, practical solutions and technological advances related to machine intelligence techniques for detecting cyberbullying across multiple social media platforms. Combines both theory and practice so that readers (beginners or experts) of this book can find both a description of the concepts and context related to the machine intelligence. Includes many case studies and applications of machine intelligence for combating cyberbullying.
Book Synopsis Support Vector Machines for Pattern Classification by : Shigeo Abe
Download or read book Support Vector Machines for Pattern Classification written by Shigeo Abe and published by Springer Science & Business Media. This book was released on 2005-12-28 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: I was shocked to see a student’s report on performance comparisons between support vector machines (SVMs) and fuzzy classi?ers that we had developed withourbestendeavors.Classi?cationperformanceofourfuzzyclassi?erswas comparable, but in most cases inferior, to that of support vector machines. This tendency was especially evident when the numbers of class data were small. I shifted my research e?orts from developing fuzzy classi?ers with high generalization ability to developing support vector machine–based classi?ers. This book focuses on the application of support vector machines to p- tern classi?cation. Speci?cally, we discuss the properties of support vector machines that are useful for pattern classi?cation applications, several m- ticlass models, and variants of support vector machines. To clarify their - plicability to real-world problems, we compare performance of most models discussed in the book using real-world benchmark data. Readers interested in the theoretical aspect of support vector machines should refer to books such as [109, 215, 256, 257].
Book Synopsis Modern Computational Intelligence Methods for the Interpretation of Medical Images by : Ryszard Tadeusiewicz
Download or read book Modern Computational Intelligence Methods for the Interpretation of Medical Images written by Ryszard Tadeusiewicz and published by Springer Science & Business Media. This book was released on 2008-01-03 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work by two accomplished Polish researchers provides medical technicians and researchers alike with detailed descriptions of up-to-date methods used for computer processing and interpretation of medical images. The broad scope of the book takes in images acquisition, storing with compression, processing, analysis, recognition and also its automatic understanding. The introduction provides a general overview of the computer vision methods designed for medical images.
Book Synopsis Deep learning in crop diseases and insect pests by : Rujing Wang
Download or read book Deep learning in crop diseases and insect pests written by Rujing Wang and published by Frontiers Media SA. This book was released on 2023-04-05 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:
