Hierarchical Neural Networks For Image Interpretation

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Hierarchical Neural Networks For Image Interpretation

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Author : Sven Behnke
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-08-21

Hierarchical Neural Networks For Image Interpretation written by Sven Behnke 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 2003-08-21 with Computers categories.

Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains. This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.

Hierarchical Neural Networks For Image Interpretation

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Author : Sven Behnke
language : en
Publisher: Springer
Release Date : 2014-03-12

Hierarchical Neural Networks For Image Interpretation written by Sven Behnke and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-12 with Computers categories.

Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains. This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.

Three Approaches To Data Analysis

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Author : Igor Chikalov
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-07-28

Three Approaches To Data Analysis written by Igor Chikalov 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 2012-07-28 with Technology & Engineering categories.

In this book, the following three approaches to data analysis are presented: - Test Theory, founded by Sergei V. Yablonskii (1924-1998); the first publications appeared in 1955 and 1958, - Rough Sets, founded by Zdzisław I. Pawlak (1926-2006); the first publications appeared in 1981 and 1982, - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected.

Transactions On Rough Sets V

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Author : James F. Peters
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-10-12

Transactions On Rough Sets V written by James F. Peters 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 2006-10-12 with Computers categories.

The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence.This fifth volume of the Transactions on Rough Sets is dedicated to the monumental life, work and creative genius of Zdzis{l}aw Pawlak, the originator of rough sets, who passed away in April 2006. It opens with a commemorative article that gives a brief coverage of Pawlak's works in rough set theory, molecular computing, philosophy, painting and poetry. Fifteen papers explore the theory of rough sets in various domains as well as new applications of rough sets. In addition, this volume of the TRS includes a complete monograph on rough sets and approximate Boolean reasoning systems that includes both the foundations as well as applications of data mining.

Medical Image Computing And Computer Assisted Intervention Miccai 2013

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Author : Kensaku Mori
language : en
Publisher: Springer
Release Date : 2013-09-20

Medical Image Computing And Computer Assisted Intervention Miccai 2013 written by Kensaku Mori and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-20 with Computers categories.

The three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 86 papers included in the second volume have been organized in the following topical sections: registration and atlas construction; microscopy, histology, and computer-aided diagnosis; motion modeling and compensation; segmentation; machine learning, statistical modeling, and atlases; computer-aided diagnosis and imaging biomarkers; physiological modeling, simulation, and planning; microscope, optical imaging, and histology; cardiology; vasculatures and tubular structures; brain segmentation and atlases; and functional MRI and neuroscience applications.

Machine Learning For Developers

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Author : Rodolfo Bonnin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-10-26

Machine Learning For Developers written by Rodolfo Bonnin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-26 with Computers categories.

Your one-stop guide to becoming a Machine Learning expert. About This Book Learn to develop efficient and intelligent applications by leveraging the power of Machine Learning A highly practical guide explaining the concepts of problem solving in the easiest possible manner Implement Machine Learning in the most practical way Who This Book Is For This book will appeal to any developer who wants to know what Machine Learning is and is keen to use Machine Learning to make their day-to-day apps fast, high performing, and accurate. Any developer who wants to enter the field of Machine Learning can effectively use this book as an entry point. What You Will Learn Learn the math and mechanics of Machine Learning via a developer-friendly approach Get to grips with widely used Machine Learning algorithms/techniques and how to use them to solve real problems Get a feel for advanced concepts, using popular programming frameworks. Prepare yourself and other developers for working in the new ubiquitous field of Machine Learning Get an overview of the most well known and powerful tools, to solve computing problems using Machine Learning. Get an intuitive and down-to-earth introduction to current Machine Learning areas, and apply these concepts on interesting and cutting-edge problems. In Detail Most of us have heard about the term Machine Learning, but surprisingly the question frequently asked by developers across the globe is, “How do I get started in Machine Learning?”. One reason could be attributed to the vastness of the subject area because people often get overwhelmed by the abstractness of ML and terms such as regression, supervised learning, probability density function, and so on. This book is a systematic guide teaching you how to implement various Machine Learning techniques and their day-to-day application and development. You will start with the very basics of data and mathematical models in easy-to-follow language that you are familiar with; you will feel at home while implementing the examples. The book will introduce you to various libraries and frameworks used in the world of Machine Learning, and then, without wasting any time, you will get to the point and implement Regression, Clustering, classification, Neural networks, and more with fun examples. As you get to grips with the techniques, you'll learn to implement those concepts to solve real-world scenarios for ML applications such as image analysis, Natural Language processing, and anomaly detections of time series data. By the end of the book, you will have learned various ML techniques to develop more efficient and intelligent applications. Style and approach This book gives you a glimpse of Machine Learning Models and the application of models at scale using clustering, classification, regression and reinforcement learning with fun examples. Hands-on examples will be presented to understand the power of problem solving with Machine Learning and Advanced architectures, software installation, and configuration.

Image Analysis And Processing Iciap 2015

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Author : Vittorio Murino
language : en
Publisher: Springer
Release Date : 2015-08-20

Image Analysis And Processing Iciap 2015 written by Vittorio Murino and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-20 with Computers categories.

The two-volume set LNCS 9279 and 9280 constitutes the refereed proceedings of the 18th International Conference on Image Analysis and Processing, ICIAP 2015, held in Genoa, Italy, in September 2015. The 129 papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in the following seven topical sections: video analysis and understanding, multiview geometry and 3D computer vision, pattern recognition and machine learning, image analysis, detection and recognition, shape analysis and modeling, multimedia, and biomedical applications.

Neural Networks For Knowledge Representation And Inference

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Author : Daniel S. Levine
language : en
Publisher: Psychology Press
Release Date : 2013-04-15

Neural Networks For Knowledge Representation And Inference written by Daniel S. Levine and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-15 with Psychology categories.

The second published collection based on a conference sponsored by the Metroplex Institute for Neural Dynamics -- the first is Motivation, Emotion, and Goal Direction in Neural Networks (LEA, 1992) -- this book addresses the controversy between symbolicist artificial intelligence and neural network theory. A particular issue is how well neural networks -- well established for statistical pattern matching -- can perform the higher cognitive functions that are more often associated with symbolic approaches. This controversy has a long history, but recently erupted with arguments against the abilities of renewed neural network developments. More broadly than other attempts, the diverse contributions presented here not only address the theory and implementation of artificial neural networks for higher cognitive functions, but also critique the history of assumed epistemologies -- both neural networks and AI -- and include several neurobiological studies of human cognition as a real system to guide the further development of artificial ones. Organized into four major sections, this volume: * outlines the history of the AI/neural network controversy, the strengths and weaknesses of both approaches, and shows the various capabilities such as generalization and discreetness as being along a broad but common continuum; * introduces several explicit, theoretical structures demonstrating the functional equivalences of neurocomputing with the staple objects of computer science and AI, such as sets and graphs; * shows variants on these types of networks that are applied in a variety of spheres, including reasoning from a geographic database, legal decision making, story comprehension, and performing arithmetic operations; * discusses knowledge representation process in living organisms, including evidence from experimental psychology, behavioral neurobiology, and electroencephalographic responses to sensory stimuli.

Pattern Recognition And Image Analysis

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Author : Antonio Pertusa
language : en
Publisher: Springer Nature
Release Date : 2023-06-24

Pattern Recognition And Image Analysis written by Antonio Pertusa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-24 with Computers categories.

This book constitutes the refereed proceedings of the 11th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2023, held in Alicante, Spain, in June 27–30, 2023. The 56 papers accepted for these proceedings were carefully reviewed and selected from 86 submissions. They deal with Machine Learning, Document Analysis, Computer Vision, 3D Computer Vision, Computer Vision Applications, Medical Imaging & Applications, Machine Learning Applications.

New Approaches In Intelligent Image Analysis

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Author : Roumen Kountchev
language : en
Publisher: Springer
Release Date : 2016-05-19

New Approaches In Intelligent Image Analysis written by Roumen Kountchev and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-19 with Technology & Engineering categories.

This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the analysis of the modeling of the developed algorithms in different application areas.