经典图论教程的中文PDF版 由A.Bondy编写，是图论的经典教材之一，这次是其经典教材的中文版

英文书籍超高清PDF，《VLSI Physical Design： From Graph Partitioning to Timing Closure》。仅供分享学习，版权归原出版社所有。如有侵权，请删除。

图像剪切的代码matlab 肺血管分割使用图切 使用以下链接准备图切优化器： 解压缩“ GCmex1.9.tar.gz”，并按照相应的说明编译图形切割的mex文件。 在Matlab中运行Demo.m文件 如果您使用该软件，则应参考以下文章： @inproceedings{zhai2016lung, title={Lung vessel segmentation in CT images using graph-cuts}, author={Zhai, Zhiwei and Staring, Marius and Stoel, Berend C}, booktitle={Medical Imaging 2016: Image Processing}, volume={9784}, pages={97842K--97849k}, year={2016}, organization={International Society for Optics and Photonics} } @article{zhai2019automatic, title={Automatic quantitati

这是关于组合优化算法的电子书，高清，最新版本，经典著作，英文版

Unity 图标制作Graph Maker

network an introduction is the famous book for network science

This book provides a definition and study of a knowledge representation and reasoning formalism stemming from conceptual graphs, while focusing on the computational properties of this formalism.

Graph

作者: Jeremy Kepner / John Gilbert 出版社: Society for Industrial & Applied Mathematics 出版年: 2011-7-14 页数: 389 定价: USD 110.00 装帧: Hardcover ISBN: 9780898719901 Graphs are among the most important abstract data types in computer science, and the algorithms that operate on them are critical to modern life. Graphs have been shown to be powerful tools for modeling complex problems because of their simplicity and generality. Graph algorithms are one of the pillars of mathematics, informing research in such diverse areas as combinatorial optimization, complexity theory, and topology. Algorithms on graphs are applied in many ways in today s world - from Web rankings to metabolic networks, from finite element meshes to semantic graphs. The current exponential growth in graph data has forced a shift to parallel computing for executing graph algorithms. Implementing parallel graph algorithms and achieving good parallel performance have proven difficult. This book addresses these challenges by exploiting the well-known duality between a canonical representation of graphs as abstract collections of vertices and edges and a sparse adjacency matrix representation. This linear algebraic approach is widely accessible to scientists and engineers who may not be formally trained in computer science. The authors show how to leverage existing parallel matrix computation techniques and the large amount of software infrastructure that exists for these computations to implement efficient and scalable parallel graph algorithms. The benefits of this approach are reduced algorithmic complexity, ease of implementation, and improved performance. Graph Algorithms in the Language of Linear Algebra is the first book to cover graph algorithms accessible to engineers and scientists not trained in computer science but having a strong linear algebra background, enabling them to quickly understand and apply graph algorithms. It also covers array-based graph algorithms, showing readers how to express canon

Review on the Knowledge Graph in Robotics Domain--知识图谱在机器人领域的应用论文