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Optimum-Path Forest: Theory, Algorithms, and Applications

Editat de Alexandre Xavier Falcao, João Paulo Papa
en Limba Engleză Paperback – 24 ian 2022
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.


  • 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)
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Specificații

ISBN-13: 9780128226889
ISBN-10: 0128226889
Pagini: 244
Dimensiuni: 152 x 229 x 15 mm
Greutate: 0.33 kg
Editura: ELSEVIER SCIENCE

Cuprins

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