CVPR2016 Paper Notes

1. Generation and Comprehension of Unambiguous Object Descriptions

This paper proposed a method that can generate an unambiguous description (known as a referring expression) of a specific object or region in an image, and which can also comprehend or interpret such an expression to infer which object is being described.

Highlights: 1. A new large-scale dataset for referring expressions. 2. Discriminative Training, given a training sample (I, R, S), where I is image, R is region and S is sentence, we train a model that outputs a high p(S|R,I), while main-training a low p(S|R’,I), whenever R’ != R. 3. Semi-supervised Training, use a small dataset to train a model. Then use this model to generate a set of descriptions for large dataset with bounding boxes. Train another ensemble model on the same small dataset and use it to verify auto-generated descriptions.

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pdfLaTeX的中文支持

直接在搜索引擎搜索 “latex”,在windows平台下,下载的大多都是pdfLaTeX,总的来说TeXstudio还是很好用的,左边有各种数学符号查阅很方便,但是pdfLaTeX对中文的支持是硬伤,百度搜索下的解决方案并不理想。下面介绍的这种方法不需要下载配置额外的包,是一个通用的中文框架。

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Python带验证码网络爬虫入门

【0】 写在前面

这篇文章写给那些有编程经验无网络经验,有python经验无爬虫经验,有网络经验无验证码识别经验的人,也算是自己从零到有,从完全小白开始奋战刷课机(一个带验证码识别的自动选课程序,学校的抢课太凶残了)两天两夜的经验总结,想做一个非常详细的教程,希望读者看完后,刷课机也基本写完了,省下时间可以多看一些其他书。

本文线索:【1】环境设置;【2】网络部分;【3】验证码识别部分。

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