Sogou Image super resolution based on sparse representation "Super-Resolution Via Sparse Representation Image"

Because recently doing image super resolution reconstruction research, lucky enough to see the Yang Jia teachers and Ma Yi teacher Daniel, published in 2010 article on image super resolution of classic essay "ImageSuper-Resolution "Sparse Representation Via", so the paper on the translation, such as improper, but also please help a lot of correction!!! Yang Jianchao, Wright John, Huang Thomas, and...
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Convolutional neural network Lenet-5 implementation

Original address: http://prog3.com/sbdm/blog/hjimce/article/details/47323463 Author: hjimce Convolutional neural network algorithm is n years ago some algorithm, just in recent years because the depth of the learning algorithm provides a new method for the training of multilayer network now and then computing capability of the computer has non year kind of computing level, a lot of current training data at the same time, so neural network algorithm again fire up, so a convolutional neural network and live up, start again, and we have to...
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Deep learning - a new wave of machine learning

Note: reproduced from the blog http://prog3.com/sbdm/blog/datoubo/article/details/8577366...
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90:Subsets II LeetCode

Given a collection of integers that might contain duplicates nums return all possible subsets.. Note: In a subset Elements must be in non-descending order.The solution set must not contain du...
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78:Subsets LeetCode

Given a set of distinct integers nums return all possible subsets.. Note: In a subset Elements must be in non-descending order.The solution set must not contain duplicate subsets. For...
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Image denoising based on deep learning (summary of the thesis)

Two thousand and fifteen Deep learning, self encoder, low illumination image enhancement Lore, Gwn Kin, Akintayo Adedotun, Soumik Sarkar. and LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement. arXiv preprint arXiv:1511.03995 (2015).,,,,,,,, and. Use depth...
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The actual machine learning notes - Microsoft wheatgrass reader and decision tree

Recent micro circle of friends, a lot of people in forwarding a game called "Microsoft wheatgrass read minds, the rules of the game is simple: to participate in the game, in the mind to a person's name, then Microsoft wheatgrass will ask you 15 questions, the answer has to be" yes "and" not "or" do not know "answer. Microsoft wheatgrass through your answer to infer decomposition, gradually narrow the scope to be speculation of the names, the principle of decision tree and these issues are similar, the user to input a series of data and answers in a given game. Decision tree...
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Machine learning - deep learning (Learning Deep)

Deep learning is a machine learning in a very close to the AI field, the motivation is established, to simulate the human brain to analyze learning neural network, recently studied the knowledge of machine learning and deep learning, this paper gives some useful information and experiences. Words Key: supervised learning and unsupervised learning, classification, regression, density estimation, clustering, deep learning, DBN Sparse, 1 supervised learning and unsupervised learning Given a set of data (inpu...
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A 2D Matrix II LeetCode240:Search

Write an efficient algorithm that searches for a value in an M x n matrix. This matrix has the following properties: 每行中的整数被按左到右的递增的整数排序…
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leetcode 74:搜索二维矩阵

写在一个 M X N 矩阵值搜索算法。该矩阵具有以下性质: 每一行中的整数都从左到右的排序,每一行的第一个整数…
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leetcode 35:搜索插入位置

给定一个排序数组和一个目标值,如果找到目标,返回该索引。如果没有,返回的索引,如果它是插入的顺序。 你可以假设没有重复的数组中…
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机器学习实战笔记--基于KNN算法的手写识别系统

利用K近邻分类器实现手写识别系统,训练数据集大约2000个样本,每个数字大约有200个样本,每个样本保存在一个txt文件中,手写体图像本身是32x32的二值图像,如下图所示: 首先,我们需要将图像格式化处理为一个向量,把一个32x32的二进制图像矩阵通过img2vector()函数转换为1x1024的向量: DEF img2vector(文件名): 回来…
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机器学习实战笔记--利用KNN算法改进约会网站的配对效果

一、案例背景 我的朋友海伦一直使用在线约会网站寻找合适自己的约会对象。尽管约会网站会推荐不同的人选,但她并不是喜欢每一个人经过一番总结,她发现曾交往过三种类型的人: (1)不喜欢的人; (2)魅力一般的人; (3)极具魅力的人; 尽管发现了上述规律,但海伦依然无法将约会网站推荐的匹配对象归入恰当的分类,她觉得可以在周一到周五约会那些魅力一般的人,而周末则更喜欢与那些极具魅力的人为伴…
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机器学习实战笔记KNN算法

一、KNN算法描述 KNN(K近邻算法),也就是K近邻算法,顾名思义,可以形象的理解为求K个最近的邻居。当k = 1时,KNN算法就成了最近邻算法,即寻找最近的那个邻居。 所谓K近邻算法,就是给定一个训练数据集,对新的输入实例,在训练数据集中找到与该实例最邻近的K个实例(就是上面提到的K个邻居),如果这K个实例的多数属于某个类,就将该输入实例分类到这个…
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Python”非ASCII字符“XE5”文件中的“报错问题

今天在编译一个Python程序的时候,一直出现”非ASCII字符“XE5”文件中的“报错问题 syntaxerror:非ASCII字符“\ XE5在上线24 knn.py文件,但没有编码声明;看到http://python.org/dev/peps/pep-0263/佛…
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leetcode34:一系列搜索

给定一个给定的目标值的起始和结束位置,给定一个排序的整数数组。 您的算法的运行时间复杂度必须是在(日志 )。 如果目标没有找到…
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