Alexandre Xavier Falcao,
João Paulo Papa
Optimum-Path Forest
Theory, Algorithms, and Applications
Paperback Engels 2022 9780128226889
Verwachte levertijd ongeveer 9 werkdagen
Samenvatting
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.
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Inhoudsopgave
<p>1. Introduction<br>2. Theoretical Background and Related Works<br>3. Real-time application of OPF-based classifier in Snort IDS<br>4. Optimum-Path Forest and Active Learning Approaches for Content-Based Medical Image Retrieval<br>5. Hybrid and Modified OPFs for Intrusion Detection Systems and Large-Scale Problems<br>6. Detecting Atherosclerotic Plaque Calcifications of the Carotid Artery Through Optimum-Path Forest<br>7. Learning to Weight Similarity Measures with Siamese Networks: A Case Study on Optimum-Path Forest<br>8. An Iterative Optimum-Path Forest Framework for Clustering<br>9. Future Trends in Optimum-Path Forest Classification</p>
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