Optimum-Path Forest : Theory, Algorithms, and Applications

Xavier Falcao, Alexandre (EDT)/ Papa, João Paulo (EDT)

Academic Press Inc（2022/01発売）

• 製本 Paperback:紙装版/ペーパーバック版／ページ数 244 p.
• 言語 ENG
• 商品コード 9780128226889
• DDC分類 006.4

Full Description

The Optimum-Path Forest (OPF) classifier was first published in 2008 in its supervised and unsupervised versions with applications in medicine and image classification. Since then, it has expanded to a variety of other applications such as remote sensing, electrical and petroleum engineering, and biology. In recent years, multi-label and semi-supervised versions were also developed to handle video classification problems. The book presents the principles, algorithms and applications of Optimum-Path Forest, giving the theory and state-of-the-art as well as insights into future directions.

Contents

1. Introduction
2. Theoretical Background and Related Works
3. Real-time application of OPF-based classifier in Snort IDS
4. Optimum-Path Forest and Active Learning Approaches for Content-Based Medical Image Retrieval
5. Hybrid and Modified OPFs for Intrusion Detection Systems and Large-Scale Problems
6. Detecting Atherosclerotic Plaque Calcifications of the Carotid Artery Through Optimum-Path Forest
7. Learning to Weight Similarity Measures with Siamese Networks: A Case Study on Optimum-Path Forest
8. An Iterative Optimum-Path Forest Framework for Clustering
9. Future Trends in Optimum-Path Forest Classification