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floyd
- 此源码是算法floyd算法的实现,里面有我自己详细解说的几个重点，对于学习图论很有帮助，用于求任意两点间最短路径和路径长度-This source is the realization of the algorithm floyd algorithm, which has my own detailed explanation of several key helpful for learning graph theory, used to find the shortest path betw
GOLPP
- GOLPP,来自南京航空航天大学,一种基于图优化的流形学习方法。-GOLPP, from nanjing university of aeronautics and astronautics, and a manifold learning method based on graph optimization.
Coloring-Problem
- Cellular Learning Automata-based Graph Coloring Problem
graph-theory
- 数据结构图论问题，初学数据结构的学生可以通过这些简单的问题熟悉数据结构课程-Data structure graph theory problem, learning data structures for students through these simple questions can be familiar with the data structure courses
asp-learning-pdf
- are given a directed graph G=(V,E) and a weight function w: E->R. We assume that G does not contain cycles of weight 0 or less.
Affinity-Learning-on-a-Tensor-Product-Graph
- Affinity Learning on a Tensor Product Graph
MATLAB
- 主要介绍了各种图论算法及其他们的matlab程序实现，这本书很好的帮助了入门的新手学习图论算法.-Introduces a variety of graph algorithms and their matlab program, this book is a good help the novice learning graph theory algorithms.
CPPAlgorithm-examples
- 好用的c++算法实现，对图论，DFS框架，排序等算法的学习非常有用-Easy to use c++ algorithms, graph theory, DFS frame, sorting algorithms, such as learning useful
Hyperspectral-Image-Classification-Through-Bilaye
- Hyperspectral image classification with limited number of labeled pixels is a challenging task. In this paper, we propose a bilayer graph-based learning framework to address this problem. For graph-based classification, how to establish the n
cPP-learning-routs
- C++ 学习路线和推荐书籍，学习基本路线图-C++ learning path with recommended books, learning the basic line of the graph
Tensorflow-Tutorial-master
- TensorFlow是谷歌基于DistBelief进行研发的第二代人工智能学习系统，其命名来源于本身的运行原理。Tensor（张量）意味着N维数组，Flow（流）意味着基于数据流图的计算，TensorFlow为张量从流图的一端流动到另一端计算过程。TensorFlow是将复杂的数据结构传输至人工智能神经网中进行分析和处理过程的系统。(TensorFlow is the second generation of artificial intelligence learning system dev
Accurate Segmentation of Cervical Cytoplasm and Nuclei Based on Multiscale Convolutional Network and Graph Partitioning
- In this paper, a multiscale convolutional network (MSCN) and graph-partitioning-based method is proposed for accurate segmentation of cervical cytoplasm and nuclei. Specifically, deep learning via the MSCN is explored to extract scale invariant f