This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pat
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. Knowledge can be symbolically represented in many ways
Graphs are ubiquitous. There is hardly any domain in which objects and their relations cannot be intuitively represented as nodes and edges in a graph. Graph theory is a well-studied sub-discipline of mathematics, with a large body of results and a
下面这个论文描述的分割算法的实现： Efficient Graph-Based Image Segmentation Pedro F. Felzenszwalb and Daniel P. Huttenlocher International Journal of Computer Vision, 59(2) September 2004. 这个程序使用彩色图像（PPM格式）并为产生的分割结果的每个区域随机分配颜色。
Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media. It addresses an important scientific and
Graph-Based Representation and Reasoning， 24th International Conference on Conceptual Structures, ICCS 2019, Marburg, Germany, July 1–4, 2019, Proceedings
title={Graph-based path planning for autonomous robotic exploration in subterranean environments},
author={Dang, Tung and Mascarich, Frank and Khattak, Shehryar and Papachristos, Christos and Alexis, Kostas}
挪威科技大学论文：用于地下环境中自主机器人探索的基于图的路径规划
