SalviaNet: A Machine Learning-based Leaf Signature Profiling and Species Identification of the Endemic Genus Salvia in Central Asia-Reference-Cited by-同舟云学术

SalviaNet: A Machine Learning-based Leaf Signature Profiling and Species Identification of the Endemic Genus Salvia in Central Asia

Published:2021-12-07 Issue: Volume: Page:
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Container-title:TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON)
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Author:

Concepcion II Ronnie¹,Turdiboev Obidjon²,Mendigoria Christan Hail³,Celep Ferhat⁴,Baikova Elena⁵,Palconit Maria Gemel³,Vicerra Ryan Rhay¹,Bandala Argel³,Dadios Elmer¹

Affiliation:

1. De La Salle University,Department of Manufacturing Engineering and Management,Manila,Philippines

2. Institute of Botany,Uzbekistan Academy of Sciences,Tashkent,Uzbekistan

3. De La Salle University,Department of Electronics and Computer Engineering,Manila,Philippinens

4. Kirikkale University,Deparment of Biology,Kirikkale,Turkey

5. Siberian Branch of the Russian Academy of Science,Central Siberian Botanical Garden,Novosibirsk,Russia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9707139/9707180/09707455.pdf?arnumber=9707455

Reference29 articles.

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2. Distribution patterns of species of the genus Astralalus L. (sect. Macrocystis, Laguropsis and Chaetodon) in the territory of Mountain Middle Asian province

3. Ecological and Geographical Analysis of Endemic Vascular Plants in Siberia and Problems of Their Conservation Ex Situ

4. Phylogeny, morphology, and biogeography ofHaplophyllum(Rutaceae), a species-rich genus of the Irano-Turanian floristic region

5. A new species of the genus Iris L. (Iridaceae Juss.) from the Ferghana Valley

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