A Study on the Potency of Hybrid Models: Detecting Diseases in Cucumber Leaves with Pre-trained CNNs and SVM-Reference-Cited by-同舟云学术

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A Study on the Potency of Hybrid Models: Detecting Diseases in Cucumber Leaves with Pre-trained CNNs and SVM

Published:2024-03-06 Issue: Volume: Page:1-4
ISSN:
Container-title:2024 12th International Electrical Engineering Congress (iEECON)
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Author:

Yodrot Teerapon¹,Sutacha Chalermkiat²,Orachon Teerapong³,Jangjongdee Nattapon¹,Boonyasuwanno Sompol¹

Affiliation:

1. Rajamangala University of Technology Rattanakosin,Faculty of Industry and Technology,Department of Electrical Engineering Technology,Prachuap Khiri Khan,Thailand

2. Ubon Ratchathani Rajabhat University,Faculty of Industrial Technology,Department of Computer Network Engineering,Ubon Ratchathani,Thailand

3. KOSEN of King Mongkut's Institute of Technology Ladkrabang,Department of Computer Engineering,Bangkok,Thailand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10537606/10537804/10537828.pdf?arnumber=10537828

Reference11 articles.

1. Plant Leaf Disease Detection using Machine Learning

2. Detection of potato diseases using image segmentation and multiclass support vector machine

3. Ensemble Learning based Plant Leaf Disease Classification Considering Deep Convolutional Features from Pre-trained CNN

4. Automated Diagnosis of Marigold Leaf Diseases using a Hybrid CNN-SVM Model

5. Automated ASPECTS Classification in Acute Ischemic Stroke using EfficientNetV2

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