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OverviewFull Product DetailsAuthor: Horst Langer (Seismologist, Senior Researcher, Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania, Osservatorio Etneo, Italy) , Susanna Falsaperla (Seismologist, Senior Researcher, Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania, Osservatorio Etneo, Italy) , Conny Hammer (Seismologist, Researcher, Schweizerischer Erdbebendienst, Eidgenössische Technische Hochschule (ETH), Zürich, Switzerland)Publisher: Elsevier Science Publishing Co Inc Imprint: Elsevier Science Publishing Co Inc Weight: 0.730kg ISBN: 9780128118429ISBN 10: 0128118423 Pages: 350 Publication Date: 20 November 2019 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsPart I: From Data to Methods 1. Patterns, Objects, and Features 2. Supervised Learning 3. Unsupervised Learning Part II: Example Applications 4. Applications with Supervised Learning 5.. Applications with Unsupervised Learning Part III: A Posteriori Analysis 6. What is a Failure? A-posteriori Analyses - Advantages and Pitfalls of Pattern Recognition Techniques 7. Software ManualsReviewsAuthor InformationHorst Langer has developed methods for automatic alert systems and early warning on Mount Etna as well as tools that are routinely operated in the monitoring room of the institute and are part of the alert system for Civil Protection. Aside from his documented experience in the application of various pattern recognition techniques, he has also published computer programs for pattern recognition. Susanna Falsaperla has a long experience in the application of pattern recognition techniques and was among the first seismologists to apply automatic classification to seismic signals on volcanoes. She has made extensive use of pattern recognition in volcanology to relate multidisciplinary data to volcanic unrest and eruptive activity. Conny Hammer has worked on automatic classification of seismic signals in continuous data streams and has introduced novel concepts and tools into the seismological community from fields of machine learning (e.g., speech processing). Her automatic recognition tools are currently implemented in daily observatory routines. Besides automatic event detection, she has focused on the application of machine learning tools in seismic site characterization. Tab Content 6Author Website:Countries AvailableAll regions |