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Python Descriptors

Python Descriptors
2018-04-16 上传大小:1.27MB
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C 7 Quick Syntax Reference, 2nd Edition

Python Descriptors, 2nd Edition Python Descriptors, 2nd Edition

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Python Descriptors, 2nd Edition

一本Python开发书籍,有助于学习Python,希望能有帮助

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Python Descriptors 无水印pdf

Python Descriptors 英文无水印pdf pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络,如有侵权,请联系上传者或csdn删除 本资源转载自网络,如有侵权,请联系上传者或csdn删除

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Python.Descriptors

This short book on Python descriptors is a collection of knowledge and ideas from many sources on dealing with and creating descriptors. And, after going through the things all descriptors have in common, the author explores ideas that have multiple ways of being implemented as well as completely new ideas never seen elsewhere before. There aren't many good resources out there for writing Python descriptors, and extremely few books. This is a sad state of affairs, as it makes it difficult for Python developers to get a really good understanding of how descriptors work and the techniques to avoid the big gotchas associated with working with them. This truly is a comprehensive guide to creating Python descriptors. As a BONUS: A pip install-able library, descriptor_tools, was written alongside this book and is an open source library on GitHub. What you'll learn What is a descriptor protocol What is attribute access and how they apply to descriptors How to make descriptors and why Which Methods are needed How to store attributes How to do Read-Only Descriptors and Writing _delete() How to explore the descriptor classes How to apply the other uses of descriptors and more Who is this book for This book is for experienced Python coders, programmers and developers. Table of Contents Part I: About Descriptors Chapter 1: What Is a Descriptor? Chapter 2: The Descriptor Protocol Chapter 3: What Are Descriptors Good For? Chapter 4: Descriptors in the Standard Library Chapter 5: Attribute Access and Descriptors Part II: Making Descriptors Chapter 6: Which Methods Are Needed? Chapter 7: Storing the Attributes Chapter 8: Read-Only Descriptors Chapter 9: Writing __delete__() Chapter 10: Descriptors are Classes Too Chapter 11: Reusing the Wheel Chapter 12: Other Uses of Descriptors in the World

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Aggregating local descriptors into a compact image representation

VLAD 图像检索方法的出处论文

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Local Invariant Feature Detectors: A Survey

Tinne Tuytelaars1 and Krystian Mikolajczyk2编写的关于不动本体特征检测的综述,很值得看,。 搞图像学必看的文章

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PCA _SIFT A More Distinctive Representation for Local Image Descriptors

PCA _SIFT A More Distinctive Representation for Local Image Descriptors 经典图像匹配论文

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color and texture descriptors

color and texture descriptors 图像研究经典论文

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Boosting binary keypoint descriptors

Boosting binary keypoint descriptors.pdf

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Boosting Binary Keypoint Descriptors 论文阅读笔记

Boosting Binary Keypoint Descriptors 论文阅读笔记

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Image Feature Detectors and Descriptors

这是关于图像挖掘的电子书,高清,最新版本,经典著作,英文版

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SAR图像处理 IEEE论文

GRSL.Contextual Descriptors for Scene Classes in Very High Resolution SAR Image

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A performance evaluation of local descriptors

A performance evaluation of local descriptors一篇经典的论文,对于学习局部算子很有帮助。

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PCA_sift paper 是sift改进方法的一篇经典文章

PCA-SIFT: A More Distinctive Representation for Local Image Descriptors

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Discriminative Learning of Local Image Descriptors

In this paper, we explore methods for learning local image descriptors from training data. We describe a set of building blocks for constructing descriptors which can be combined together and jointly optimized so as to minimize the error of a nearestneighbor classifier. We consider both linear and nonlinear transforms with dimensionality reduction, and make use of discriminant learning techniques such as Linear Discriminant Analysis (LDA) and Powell minimization to solve for the parameters. Using these techniques, we obtain descriptors that exceed state-of-the-art performance with low dimensionality. In addition to new experiments and recommendations for descriptor learning, we are also making available a new and realistic ground truth data set based on multiview stereo data.

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Color_descriptors

模式识别 图像识别 Abstract—This paper presents an overview of color and texture descriptors that have been approved for the Final Committee Draft of the MPEG-7 standard. The color and texture descriptors that are described in this paper have undergone extensive evaluation and development during the past two years. Evaluation criteria include effectiveness of the descriptors in similarity retrieval, as well as extraction, storage, and representation complexities. The color descriptors in the standard include a histogram descriptor that is coded using the Haar transform, a color structure histogram, a dominant color descriptor, and a color layout descriptor. The three texture descriptors include one that characterizes homogeneous texture regions and another that represents the local edge distribution. A compact descriptor that facilitates texture browsing is also defined. Each of the descriptors is explained in detail by their semantics, extraction and usage. Effectiveness is documented by experimental results.

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Simple 2D and 3D Shape Descriptors

可用于放疗计划系统各种靶区参数的计算,文档中给出了各种参数的计算公式

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Granularity-tunable Gradients Partition (GGP) Descriptors

本论文表述了一种新的行人检测方法,区别于传统的行人检测方法,使得行人检测系统的可靠性大大提高。

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PSIFT matlab code

Local Pyramidal Descriptors for Image Recognition 此篇论文matlab代码,作者个人网页下载

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ACM Subject Categories and Descriptors, general terms1998

这是ACM1998年版Classification Codes,可用于计算机方向论文中Subject Categories and Descriptors, general terms的描述,此资源从ACM官网下载,为1998年版,需要者可从该资源网页链接中下载最新版。

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Python Descriptors

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