Optimum-Path Forest: Theory, Algorithms, and Applications

Optimum-Path Forest: Theory, Algorithms, and Applications 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. Presents the first book on Optimum-path Forest Shows how it can be used with Deep Learning Gives a wide range of applications Includes the methods, underlying theory and applications of Optimum-Path Forest (OPF) INDICE: 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

• ISBN: 978-0-12-822688-9
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 244
• Fecha Publicación: 24/01/2022
• Nº Volúmenes: 1
• Idioma: Inglés