Computational botany : methods for automated species identification. / Paolo Remagnino
By: Remagnino, Paolo,, autor
Material type:
E-bookPublisher: [Berlin] : Springer, 2017Description: 1 recurso en línea.ISBN: 3662537451; 9783662537459.Subject: Inteligencia artificial
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QK46.5.E4 R463 2017 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.20022641 |
Browsing Madrid Digital shelves, Shelving location: Acceso Electrónico (UEM) Close shelf browser (Hides shelf browser)
| QK46.5.D58 2023 EB Halophyte Plant Diversity and Public Health | QK46.5.D58 A385 2014 EB Biotechnology and Biodiversity | QK46.5.D58 G462 2016 EB Genetic Diversity and Erosion in Plants : Case Histories | QK46.5.E4 R463 2017 EB Computational botany : methods for automated species identification. | QK47 2013 EB Strasburger's Plant Sciences : Including Prokaryotes and Fungi | QK47 2014 EB Progress in Botany Vol. 75 | QK47 2017 EB Progress in botany 78 |
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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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