FloraNet: An Approach to Prediction of Sea Buckthorn Disease based on a Convolutional Neural Network and a Random Forest Method-Reference-Cited by-同舟云学术

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FloraNet: An Approach to Prediction of Sea Buckthorn Disease based on a Convolutional Neural Network and a Random Forest Method

Published:2024-05-24 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 5th International Conference for Emerging Technology (INCET)
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Author:

Pushpakumari J.¹,Bhaskar Nuthanakanti²,Divya G.³,Kanthi Murali⁴,Srujan Raju K.²,Narasimharao Jonnadula²

Affiliation:

1. VNRVJIET,Dept. of Computer Science and Engineering (AIML & IOT),Hyderabad,Telangana,India

2. CMR Technical Campus,Dept. of Computer Science and Engineering,Hyderabad,Telangana,India

3. CMR Technical Campus,Dept. of Information Technology,Hyderabad,Telangana,India

4. CMR Technical Campus,Department of Computer Science & Engineering (Data Science),Hyderabad,Telangana,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592862/10592849/10593039.pdf?arnumber=10593039

Reference25 articles.

1. Abundance of active ingredients in sea-buckthorn oil

2. Harvesting technologies for sea buckthorn fruit

3. Genotypic and Morphometric Effect on Fruit Oil Content in Seventeen Natural Population of Seabuckthorn (Hippophae rhamnoides L.) from Trans-Himalaya

4. Sea-buckthorn: a species with a variety of uses, especially in land reclamation

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