Graph-Based Representations in Pattern Recognition

Discover the fascinating world of graph-based representations in pattern recognition with the insightful book Graph-Based Representations in Pattern Recognition by Donatello Conte. Published by Springer Nature Switzerland AG in 2019, this paperback edition spans 247 pages, offering a comprehensive exploration of advanced topics in the field.

This essential read delves into critical areas such as graph edit distance, graph matching, and machine learning applications for graph problems. Additionally, it covers network and graph embedding, spectral graph issues, and parallel algorithms tailored for graph challenges. Perfect for researchers and practitioners alike, this book equips you with the knowledge needed to navigate and excel in the evolving landscape of pattern recognition.

Enhance your understanding and application of graph theory in various domains by adding this valuable resource to your collection.