mxyzptlk的博客

Beautiful Vim Cheat-Sheet by Max Cantor 非常NICE的vim速查表，高清5925*4125，在作者博客上售价25刀，参见：http://vimcheatsheet.com/

作者miguelgrinberg，基于最新的 Flask 和 Python3 等新特性。非常棒的flask教程。

Introduction to Computation and Programming Using Python 第四版 核对勘误至18年1月 The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters.

Programming Python 第四版 核对勘误至18年1月 If you've mastered Python's fundamentals, you're ready to start using it to get real work done. Programming Python will show you how, with in-depth tutorials on the language's primary application domains: system administration, GUIs, and the Web. You'll also explore how Python is used in databases, networking, front-end scripting layers, text processing, and more. This book focuses on commonly used tools and libraries to give you a comprehensive understanding of Python’s many roles in practical, real-world programming. You'll learn language syntax and programming techniques in a clear and concise manner, with lots of examples that illustrate both correct usage and common idioms. Completely updated for version 3.x, Programming Python also delves into the language as a software development tool, with many code examples scaled specifically for that purpose.

Learning Python 第五版 核对勘误至18年1月 Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages. Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code.

Drug name recognition (DNR), which seeks to recognize drug mentions in unstructured medical texts and classify them into pre-defined categories, is a fundamental task of medical information extraction, and is a key component of many medical relation extraction systems and applications. A large number of efforts have been devoted to DNR, and great progress has been made in DNR in the last several decades. We present here a comprehensive review of studies on DNR from various aspects such as the challenges of DNR, the existing approaches and resources for DNR, and possible directions.

In many pattern recognition problems such as handwritten character recognition, it would be a challenge to design a good classification function, which can eliminate irrelevant variabilities among objects of the same class, while at the same time, being able to identify meaningful differences between objects of different classes. For example, in order for an automatic technique to “recognize” a handwritten digit, the incoming digit pattern needs to be accurately classified into one out of ten possible categories (from “0” to “9”). One straightforward yet inefficient way of implementation would be to match the pattern with a set of prototypes, where almost all possible instances (e.g., different sizes, angles, skews, etc.) of the digit in each category must be stored, according to a certain distance measure. Consequently, the pattern will be classified into the category where the closest match with one of its prototype instances was found. This approach would lead to impractically large prototype sets in order to achieve high recognition accuracy. An alternative method is to use only one prototype for each category, where different “deformed” instances of the same prototype can be generated by geometric transformations (e.g., thickened or rotated) during the matching process so as to best fit the incoming digit pattern. To this end, the concept of Lie operators for the transformations would be applicable.

Optical Character Recognition (OCR) using Android has been received a great attention. In all these efforts a flat document is selected for OCRing and non-flat documents are ignored. Labels mounted on cylindrical surfaces such as wine bottle, pill box, cans, etc, are examples of non-flat documents. The goal of this research effort is to perform optical character recognition on a non-flat document. To be more specific, we investigate OCRing of a cylindrical pill box label. Two pictures of the label are needed for the OCRing. The methodology was applied on 30 synthesized non-flat labels and on average, the system was able to accurately recognize 92.4% of the characters.

Medical system based on image processing is playing an important role in clinical medicine today. However, the checking for label on powder medicine bottle is still being done manually by pharmacists in the injection pharmacy admixture preparation process. In this article, an automated method is proposed for checking the curved label of powder medicine bottle. The proposed method mainly consists of two stages. The first one is a register system, in this stage all the available labels are collected and processed to establish template database. In the second stage, the label images captured in real-time are named target images. Then, match the target images with template images sequentially and finally output the best matching result. The results demonstrate that the method proposed can automatically and effectively check the label of powder medicine bottle.

Image processing algorithms based on the mammalian visual cortex are powerful tools for extraction information and manipulating images. This book reviews the neural theory and translates them into digital models. Applications are given in areas of image recognition, foveation, image fusion and information extraction. The third edition reflects renewed international interest in pulse image processing with updated sections presenting several newly developed applications. This edition also introduces a suite of Python scripts that assist readers in replicating results presented in the text and to further develop their own applications.