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Computational Botany Methods For Automated Species Identification 1st Ed 2017 Paolo Remagnino

  • SKU: BELL-5701100
Computational Botany Methods For Automated Species Identification 1st Ed 2017 Paolo Remagnino
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Computational Botany Methods For Automated Species Identification 1st Ed 2017 Paolo Remagnino instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 3.07 MB
Pages: 114
Author: Paolo Remagnino, Simon Mayo, Paul Wilkin, James Cope, Don Kirkup
ISBN: 9783662537435, 3662537435
Language: English
Year: 2017
Edition: 1st ed. 2017

Product desciption

Computational Botany Methods For Automated Species Identification 1st Ed 2017 Paolo Remagnino by Paolo Remagnino, Simon Mayo, Paul Wilkin, James Cope, Don Kirkup 9783662537435, 3662537435 instant download after payment.

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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