Integrating Convolutional Neural Networks and Random Forest for Accurate Grading of Rice Spot Disease Severity-Reference-Cited by-同舟云学术

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Integrating Convolutional Neural Networks and Random Forest for Accurate Grading of Rice Spot Disease Severity

Published:2024-05-24 Issue: Volume: Page:1-4
ISSN:
Container-title:2024 5th International Conference for Emerging Technology (INCET)
language:
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Author:

Kaur Arshleen¹,Sharma Rishabh¹,Upadhyay Deepak²,Aeri Manisha³

Affiliation:

1. Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab,India

2. Graphic Era Hill University,Computer Science and Engineering,Dehradun,Uttarakhand,India,248002

3. Era Deemed to be University,Computer Science and Engineering Graphic,Dehradun,Uttarakhand,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592862/10592849/10593360.pdf?arnumber=10593360

Reference14 articles.

1. Improved Glioma Grading Using Deep Convolutional Neural Networks

2. Novel solutions for an old disease: Diagnosis of acute appendicitis with random forest, support vector machines, and artificial neural networks

3. Analysis of Alzheimer’s Disease Based on the Random Neural Network Cluster in fMRI

4. Mustard Downy Mildew Disease Severity Detection using Deep Learning Model

5. A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task

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