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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM24515

WILD PLANT PODUCE EDIBLITY PREDICTION

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM24515

Volume:

7 |

7 |

Jul 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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DSGBB

Dr. SHANKARA GOWDA B B

KSSM

KOTRU SWAMY S M

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Abstract

The medication business balances the environment as well as farming efficiency and manageability. Botanists are keen on the minor departure from leaf qualities as it assists them with doing a similar to the investigation on plants. Acknowledgment a Plant from pictures is a difficult PC vision task. The different kinds of difficulties are many pieces of the plant, which should be distinguished, are additionally assorted in nature with high intra class varieties and little entomb class varieties. Albeit the exploration on programmed plant scientific categorization has delivered productive outcomes, however those models are still distant from the prerequisites of a completely robotized natural reconnaissance situation.

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Dr. SHANKARA GOWDA B B, KOTRU SWAMY S M, "WILD PLANT PODUCE EDIBLITY PREDICTION," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 7, Jul 2023. https://doi.org/10.55041/IJSREM24515

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Publication Date

7/14/2023

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Double-Blind Peer Review

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The authors declare no conflict of interest related to this research work.

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