Automated Taxon Identification in Systematics

Theory, Approaches and Applications
Herausgeber: Macleod, Norman

• Broschiertes Buch

Produktbeschreibung

Automated Taxon Identification in Systematics shows how automated identification can be applied to various organismal groups. It is the first text to address the interface between the species recognition question in the biological sciences and the class recognition problem in mathematics and statistics. It will be of interest to taxonomists as well as computational professionals who focus on the biological sciences. Featuring high-profile contributors, the text presents current trends in quantitative approaches to group-recognition challenges, discusses the identification capabilities of current software systems, and evaluates applications of this technology to present and future problems.

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Produktdetails

• Verlag: CRC Press
• Seitenzahl: 368
• Erscheinungstermin: 17. Oktober 2019
• Englisch
• Abmessung: 251mm x 178mm x 20mm
• Gewicht: 885g
• ISBN-13: 9780367388836
• ISBN-10: 0367388839
• Artikelnr.: 58053566

Autorenporträt

Norman MacLeod

Inhaltsangabe

Introduction. The Need for Automated Approaches to Species Identification.
Is Automated Species Identification Feasible? Natural Object Recognition:
Machines Vs. Humans. Homology and Morphometrics: An Old Theme Revisited.
Plastic Self-Organizing Maps. Decision Trees: A Machine-learning
Methodology to Analyze the Relationship between Skeletal Morphology and
Ecological Adaptations. DAISY: A Practical Computer Based Tool for
Semi-Automated Species Identification. Introducing SPIDA-web: An Automated
Identification System for Biological Species. Automated Extraction and
Analysis of Morphological Features for Species Identification. Pattern
Recognition for Ecological Science and Environmental Monitoring.
Identification of Botanical Taxa using Artificial Neural Networks. Use of
Neural Nets in Identification of Spheniscid Species. Drawing the Line: the
Differentiation Between Morphological Plasticity and Interspecific
Variation. Summary and Prospectus.