Automated Taxon Identification in Systematics: Theory, Approaches and Applications

Front Cover
Norman MacLeod
CRC Press, Jul 23, 2007 - Science - 368 pages
1 Review
The automated identification of biological objects or groups has been a dream among taxonomists and systematists for centuries. However, progress in designing and implementing practical systems for fully automated taxon identification has been frustratingly slow. Regardless, the dream has never died. Recent developments in computer architectures and innovations in software design have placed the tools needed to realize this vision in the hands of the systematics community, not several years hence, but now. And not just for DNA barcodes or other molecular data, but for digital images of organisms, digital sounds, digitized chemical data - essentially any type of digital data.

Based on evidence accumulated over the last decade and written by applied researchers, Automated Taxon Identification in Systematics explores contemporary applications of quantitative approaches to the problem of taxon recognition. The book begins by reviewing the current state of systematics and placing automated taxon identification in the context of contemporary trends, needs, and opportunities. The chapters present and evaluate different aspects of current automated system designs. They then provide descriptions of case studies in which different theoretical and practical aspects of the overall group-identification problem are identified, analyzed, and discussed.

A recurring theme through the chapters is the relationship between taxonomic identification, automated group identification, and morphometrics. This collection provides a bridge between these communities and between them and the wider world of applied taxonomy. The only book-length treatment that explores automated group identification in systematic context, this text also includes introductions to basic aspects of the fields of contemporary artificial intelligence and mathematical group recognition for the entire biological community.
  

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Contents

Chapter 1 Introduction
1
Chapter 2 Digital Innovation and Taxonomys Finest Hour
9
Man versus Machine
25
Chapter 4 Neural Networks in Brief
47
An Old Theme Revisited
69
Concepts and Applications
83
A Practical ComputerBased Tool for SemiAutomated Species Identification
101
Chapter 8 Automated Extraction and Analysis of Morphological Features for Species Identification
115
A MachineLearning Method for Characterizing Morphological Patterns Resulting from Ecological Adaptation
261
The Yeasts and the BioloMICS Software as a Case Study
277
Chapter 17 Automatic Measurement of Honeybee Wings
289
Chapter 18 Good Performers Know Their Audience Identification and Characterization of Pitch Contours in Infant and ForeignerDirected Speech
299
Appendix 1
311
Appendix 2
313
Appendix 3
315
Appendix 4
319

Wavelets Neural Networks and Internet Accessibility in an ImageBased Automated Identification System
131
Face Recognition in Wasps
153
An Initial Report
189
Chapter 12 Plant Identification from Characters and Measurements Using Artificial Neural Networks
207
Can Reliable Taxonomic Identifications Be Made Using Isolated Foot Bones?
225
Chapter 14 A New SemiAutomatic Morphometric Protocol for Conodonts and a Preliminary Taxonomic Application
239
Appendix 5
321
Subject Index
329
Taxon Index
337
Back cover
351
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