Prediction of Grape Leaf Black Rot Damaged Surface Percentage Using Hybrid Linear Discriminant Analysis and Decision Tree-Reference-Cited by-同舟云学术

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Prediction of Grape Leaf Black Rot Damaged Surface Percentage Using Hybrid Linear Discriminant Analysis and Decision Tree

Published:2021-06-25 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on Intelligent Technologies (CONIT)
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Author:

Alajas Oliver John,Concepcion Ronnie,Dadios Elmer,Sybingco Edwin,Mendigoria Christan Hail,Aquino Heinrick

Funder

Research and Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9497779/9498265/09498518.pdf?arnumber=9498518

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Grape leaf disease prediction using Sine Cosine Butterfly Optimization-based deep neuro fuzzy network;Multimedia Tools and Applications;2023-11-07

2. Deep Learning Approaches for Plant Disease Management: A State-of-the-Art Analysis;2023 7th International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS);2023-11-02

3. Intelligent Monitoring System to Assess Plant Development State Based on Computer Vision in Viticulture;Computation;2023-09-03

4. From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2;Applications in Plant Sciences;2023-09

5. Construction of a grape quality index from RGB images of crates;Sixteenth International Conference on Quality Control by Artificial Vision;2023-07-28

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