A deep learning-based approach for the identification of selected species of genus Euphorbia L.-Reference-Cited by-同舟云学术

A deep learning-based approach for the identification of selected species of genus Euphorbia L.

Published:2023-05-19 Issue:5 Volume:15 Page:2435-2444
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Gautam Neelam^ORCID,Sidhu M. C.^ORCID,Kumar Anuj^ORCID

Funder

Human Resource Development Group

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41870-023-01248-0.pdf

Reference38 articles.

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2. Hanz DM, Beloiu M, Wipfler R et al (2022) High species turnover and low intraspecific trait variation in endemic and non-endemic plant species assemblages on an oceanic island. J Veg Sci 33(1):1–11. https://doi.org/10.1111/jvs.13120

3. Hamilton AC (2004) Medicinal plants, conservation and livelihoods. Biodiv Conser 13:1477–1517. https://doi.org/10.1023/B:BIOC.0000021333.23413.42

4. Dorsey BL, Haevermans T, Aubriot X et al (2013) Phylogenetics, morphological evolution and classification of Euphorbia subgenus Euphorbia. Taxon 62:291–315. https://doi.org/10.12705/622.1

5. Ernst M, Grace OM, Saslis-Lagoudakis CH et al (2015) Global medicinal uses of Euphorbia L. (Euphorbiaceae). J Ethnopharm 176:90–101. https://doi.org/10.1016/j.jep.2015.10.025

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