Digital image processing, Gonzalez & Woods, 3rd edition

Learning Image Processing with OpenCV

林肯实验室对STAP在AMTI 和GMTI雷达中的应用的综述PPT，很全面，具有实用价值

本书介绍了现代数码相机的基本原理，基本覆盖到了各个硬件模块和少数算法的介绍。但本书的着重点是Image Sensor的成像原理、artifacts和noise来源，以及对策，想了解相关知识的可以仔细研读其相关部分。

matlab边缘增强的代码 image-processing Matlab实现的可执行程序 实现ppm、pgm以及jpg等格式图像的基本处理 通过用matlab编写数字图像处理的基本算法GUI程序，实现对图像读写、缩放、旋转倾斜的基本处理，以及图像增强、平滑处理中的低通滤波和矩形滤波方法；用梯度方法实现边缘检测，比较了Sobel、Roberts和Prewitt算子的不同，也尝试了高斯拉普拉斯算子。同时在完成实验要求之余，了解了YUV格式和图像负片转化。最后，对图像用matlab导出了matlab内置app和可安装的独立运行的可执行文件。实验为了避免在matlab中出现乱码，GUI界面和代码注释都用采用英文。

CommonGen：面向生成常识推理的受限文本生成挑战 @article{lin2019comgen, author = {Bill Yuchen Lin and Wangchunshu Zhou and Ming Shen and Pei Zhou and Chandra Bhagavatula and Yejin Choi and Xiang Ren}, title = {CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning}, journal = {Findings of EMNLP}, year = {2020} } CommonGen是一个新的受约束文本生成数据集，它需要不同种类的常识来生成有关日常场景的句子，并因此针对生成型

最新版的《Perl程序设计<第四版>》！Perl创始人唯一相关书籍！学习Perl编程语言必备！ Programming Perl: Unmatched power for text processing and scripting By Tom Christiansen, brian d foy, Larry Wall, Jon Orwant Ph.D. Fourth edition 2012 | 1176 Pages | ISBN: 0596004923 | PDF | 20 MB Adopted as the undisputed Perl bible soon after the first edition appeared in 1991, Programming Perl is still the go-to guide for this highly practical language. Perl began life as a super-fueled text processing utility, but quickly evolved into a general purpose programming language that’s helped hundreds of thousands of programmers, system administrators, and enthusiasts, like you, get your job done. In this much-anticipated update to "the Camel," three renowned Perl authors cover the language up to its current version, Perl 5.14, with a preview of features in the upcoming 5.16. In a world where Unicode is increasingly essential for text processing, Perl offers the best and least painful support of any major language, smoothly integrating Unicode everywhere—including in Perl’s most popular feature: regular expressions. Important features covered by this update include: New keywords and syntax I/O layers and encodings New backslash escapes Unicode 6.0 Unicode grapheme clusters and properties Named captures in regexes Recursive and grammatical patterns Expanded coverage of CPAN Current best practices

精确计算球体和网格单元的重叠体积和面积 计算球体与通常使用的网格元素（例如四面体或六面体）之一的相交或重叠体积是令人惊讶的挑战。 这个仅标头的库实现了一种数字健壮的方法来确定此卷。 该代码中使用的数学表达式和算法在进行了描述。 因此，如果您在产生任何出版物的项目中使用该代码，请引用本文。 利用用于计算重叠体积的概念和例程，也可以使用此库来计算球体的相交或重叠区域以及网格元素的小平面。 用法 支持的原语 重叠计算直接支持以下元素类型： 四面体（4个节点/顶点，数据类型为Tetrahedron ） 五面体/楔形/三角棱镜（5个节点/顶点，数据类型为Wedge ） hexahedra（6个节点/顶点，数据类型为Hexahedron ） 元素必须是凸形的，并且必须指定为三维节点/顶点的列表，而球体（数据类型Sphere ）则需要一个中心点和半径。 节点排序 重叠库的元素类型遵循项目的

This textbook introduces sparse and redundant representations with a focus on applications in signal and image processing. The theoretical and numerical foundations are tackled before the applications are discussed. Mathematical modeling for signal sources is discussed along with how to use the proper model for tasks such as denoising, restoration, separation, interpolation and extrapolation, compression, sampling, analysis and synthesis, detection, recognition, and more. The presentation is elegant and engaging. Sparse and Redundant Representations is intended for graduate students in applied mathematics and electrical engineering, as well as applied mathematicians, engineers, and researchers who are active in the fields of signal and image processing.

Spoken Language Processing(黄学东,洪小文)