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Titlebook: Natural Image Statistics; A Probabilistic Appr Aapo Hyv?rinen,Jarmo Hurri,Patrik O. Hoyer Book 2009 Springer-Verlag London 2009 Computation

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發(fā)表于 2025-3-21 19:04:53 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Natural Image Statistics
副標(biāo)題A Probabilistic Appr
編輯Aapo Hyv?rinen,Jarmo Hurri,Patrik O. Hoyer
視頻videohttp://file.papertrans.cn/662/661769/661769.mp4
概述Very first book on this topic.Accessible to a wide audience from different disciplines.Topic is very timely and of increasing importance.Includes supplementary material:
叢書(shū)名稱Computational Imaging and Vision
圖書(shū)封面Titlebook: Natural Image Statistics; A Probabilistic Appr Aapo Hyv?rinen,Jarmo Hurri,Patrik O. Hoyer Book 2009 Springer-Verlag London 2009 Computation
描述Aims and Scope This book is both an introductory textbook and a research monograph on modeling the statistical structure of natural images. In very simple terms, “natural images” are photographs of the typical environment where we live. In this book, their statistical structure is described using a number of statistical models whose parameters are estimated from image samples. Our main motivation for exploring natural image statistics is computational m- eling of biological visual systems. A theoretical framework which is gaining more and more support considers the properties of the visual system to be re?ections of the statistical structure of natural images because of evolutionary adaptation processes. Another motivation for natural image statistics research is in computer science and engineering, where it helps in development of better image processing and computer vision methods. While research on natural image statistics has been growing rapidly since the mid-1990s, no attempt has been made to cover the ?eld in a single book, providing a uni?ed view of the different models and approaches. This book attempts to do just that. Furthermore, our aim is to provide an accessible intr
出版日期Book 2009
關(guān)鍵詞Computational Neuroscience; Excel; Information; Machine Learning; Neuroscience; Stereo; Vision; Visual Neur
版次1
doihttps://doi.org/10.1007/978-1-84882-491-1
isbn_softcover978-1-84996-844-7
isbn_ebook978-1-84882-491-1Series ISSN 1381-6446
issn_series 1381-6446
copyrightSpringer-Verlag London 2009
The information of publication is updating

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Introductionso, the theory can be applied on engineering problems but we do not go into the details of such applications in this book..This introductory chapter explains the motivation for modeling the statistical structure of natural images, and discusses some basic concepts related to vision and information processing.
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Lateral Interactions and Feedbackkage, of coefficients in the higher stage. Second, we will consider a lateral interaction phenomenon: end-stopping in simple cells. Finally, we will discuss the relationship of the principle of predictive coding to these phenomena.
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Book 2009mple terms, “natural images” are photographs of the typical environment where we live. In this book, their statistical structure is described using a number of statistical models whose parameters are estimated from image samples. Our main motivation for exploring natural image statistics is computat
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Energy Correlation of Linear Features and?NormalizationThey turn out to be extremely interesting both from the viewpoint of computational neuroscience and image processing. Like in the case of ICA, the models proposed here are still very far from providing a complete description of natural image statistics, but each model does exhibit some very interesting new phenomena just like ICA.
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1381-6446 ludes supplementary material: Aims and Scope This book is both an introductory textbook and a research monograph on modeling the statistical structure of natural images. In very simple terms, “natural images” are photographs of the typical environment where we live. In this book, their statistical s
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