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falcao optimum path forest theory algorithms app 2022

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Textbook in PDF format 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. Biography of the editors Preface Introduction References Theoretical background and related works Introduction The optimum-path forest framework Theoretical background Supervised learning OPF using complete graph OPF using k-nn graph Semisupervised learning Unsupervised learning Applications Supervised Improvements in training Improvements in classification Variations in learning Biological sciences Biometrics Electrical engineering Geosciences and remote sensing Image and video analysis Materials engineering Medicine Network security Feature selection Petroleum exploration Other applications Voice recognition Semisupervised Unsupervised Electrical engineering Image and video processing Medicine Network security Remote sensing images Other applications Conclusions and future trends Acknowledgments References Real-time application of OPF-based classifier in Snort IDS Introduction Intrusion detection systems Detection approaches in IDS Anomaly detection techniques Types of IDS Open source IDS Snort Machine learning Learning methods Algorithms Optimum-path forest Metrics for effectiveness analysis Methodology CICIDS data set Data set balancing ml_classifiers plugin Network traffic flow management Classification of network traffic flows Plugin configuration Experiments and results First stage of experiments Naive Bayes Decision tree Random forests Support vector machine Optimum-path forest AdaBoost Comparison of classification techniques Second stage of experiments DoS slowloris DoS SlowHTTPTest DoS hulk Port scan SSH brute force Final considerations Future works Acknowledgments References Optimum-path forest and active learning approaches for content-based medical image retrieval Introduction Methodology Active learning strategy Experiments Results and discussion Conclusion Funding and acknowledgments References Hybrid and modified OPFs for intrusion detection systems and large-scale problems Introduction Modified OPF-based IDS using unsupervised learning and social network concept Hybrid IDS using unsupervised OPF based on MapReduce approach Hybrid IDS using modified OPF and selected features Modified OPF using Markov cluster process algorithm Modified OPF based on coreset concept Partitioning step Sampling step Enhancement of MOPF using k-medoids algorithm References Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest Introduction Theoretical background Computer-aided diagnosis of atherosclerotic lesions Optimum-path forest Optimum-path forest classifier Probabilistic optimum-path forest Optimum-path forest-based approach for anomaly detection Fuzzy optimum-path forest Optimum-path forest based on k-connectivity Methodology Data set Features set Metrics Experimental setup Experimental results Classification Statistical analysis Computational burden Conclusions and future works References Learning to weight similarity measures with Siamese networks: a case study on optimum-path forest Introduction Theoretical background Optimum-path forest Training step Testing step Siamese networks Methodology Proposed approach Data sets Experimental setup Experimental results BBC News Caltech Silhouettes MPEG- Semeion Conclusion References An iterative optimum-path forest framework for clustering Introduction Related work The iterative optimum-path forest framework Seed set selection Clustering by optimum-path forest Seed recomputation Returning the forest with lowest total path-cost Algorithm outline Application to object delineation Experimental results Object delineation by iterative dynamic trees Analysis on road networks Experiments on synthetic data sets Conclusions and future work Acknowledgments References Future trends in optimum-path forest classification References Index Back Cover

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falcao optimum path forest theory algorithms app 2022