From the Content.- Introduction.- Morphometrics: a Brief Review.- Feature Extraction.- Machine Learning for Plant Leaf Analysis.
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Destinations, frais et délaisVendeur : Buchpark, Trebbin, Allemagne
Etat : Sehr gut. Zustand: Sehr gut | Seiten: 114 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 27227281/12
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Describes cutting-edge methods for feature extraction, analysis and classification of leavesDiscusses machine learning techniques for plant leaf analysisAnalyzes the performance of plant scientists carrying out simply leaf recognition tasks. N° de réf. du vendeur 130359591
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9783662537435_new
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 114 pp. Englisch. N° de réf. du vendeur 9783662537435
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Vendeur : Brook Bookstore On Demand, Napoli, NA, Italie
Etat : new. Questo è un articolo print on demand. N° de réf. du vendeur 4e74f6abf921e6977c91e45c779640ef
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9783662537435
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Hardcover. Etat : Brand New. 124 pages. 9.75x6.25x0.50 inches. In Stock. N° de réf. du vendeur x-3662537435
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