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Computational Botany [electronic resource] : Methods for Automated Species Identification / by Paolo Remagnino, Simon Mayo, Paul Wilkin, James Cope, Don Kirkup.

By: Remagnino, Paolo [author.].
Contributor(s): Mayo, Simon [author.] | Wilkin, Paul [author.] | Cope, James [author.] | Kirkup, Don [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: VIII, 114 p. 38 illus., 20 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662537459.Subject(s): Computational intelligence | Botany | Image processing—Digital techniques | Computer vision | Computational Intelligence | Plant Science | Computer Imaging, Vision, Pattern Recognition and GraphicsAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
From the Content -- Introduction -- Morphometrics: a Brief Review -- Feature Extraction -- Machine Learning for Plant Leaf Analysis.
In: Springer Nature eBookSummary: This book discusses innovative methods for mining information from images of plants, especially leaves, and highlights the diagnostic features that can be implemented in fully automatic systems for identifying plant species. Adopting a multidisciplinary approach, it explores the problem of plant species identification, covering both the concepts of taxonomy and morphology. It then provides an overview of morphometrics, including the historical background and the main steps in the morphometric analysis of leaves together with a number of applications. The core of the book focuses on novel diagnostic methods for plant species identification developed from a computer scientist’s perspective. It then concludes with a chapter on the characterization of botanists' visions, which highlights important cognitive aspects that can be implemented in a computer system to more accurately replicate the human expert’s fixation process. The book not only represents an authoritative guide to advanced computational tools for plant identification, but provides experts in botany, computer science and pattern recognition with new ideas and challenges. As such it is expected to foster both closer collaborations and further technological developments in the emerging field of automatic plant identification.
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From the Content -- Introduction -- Morphometrics: a Brief Review -- Feature Extraction -- Machine Learning for Plant Leaf Analysis.

This book discusses innovative methods for mining information from images of plants, especially leaves, and highlights the diagnostic features that can be implemented in fully automatic systems for identifying plant species. Adopting a multidisciplinary approach, it explores the problem of plant species identification, covering both the concepts of taxonomy and morphology. It then provides an overview of morphometrics, including the historical background and the main steps in the morphometric analysis of leaves together with a number of applications. The core of the book focuses on novel diagnostic methods for plant species identification developed from a computer scientist’s perspective. It then concludes with a chapter on the characterization of botanists' visions, which highlights important cognitive aspects that can be implemented in a computer system to more accurately replicate the human expert’s fixation process. The book not only represents an authoritative guide to advanced computational tools for plant identification, but provides experts in botany, computer science and pattern recognition with new ideas and challenges. As such it is expected to foster both closer collaborations and further technological developments in the emerging field of automatic plant identification.

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