Deep Learning-Based Diagnosis of Rice Sheath Rot Disease: A Wavelet-Filtered Approach for Feature Extraction and Analysis-Reference-Cited by-同舟云学术

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Deep Learning-Based Diagnosis of Rice Sheath Rot Disease: A Wavelet-Filtered Approach for Feature Extraction and Analysis

Published:2024-04-18 Issue: Volume: Page:1-8
ISSN:
Container-title:2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS)
language:
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Author:

Atheeswaran Athiraja¹,Maheshkumar K²,Jayareka K.S.³,Janani B⁴,Lakshmanan K⁵,Sobiyaa P⁶

Affiliation:

1. Malla Reddy College of Engineering,Department of CSE,Hyderabad,Telangana,India

2. Bannari Amman Institute of Technonology,Dept of Computer Science and Design,Erode,Tamilnadu,India

3. Sona College of Technology,Dept of Computer Science and Engineering,Salem,Tamilnadu,India

4. Dr.NGP Institute of Technology,Department of Computer science and business systems,Coimbatore,Tamilnadu,India

5. Hindusthan College of Engineering and Technology,Dept of CSE,Coimbatore,Tamilnadu,India

6. Bannari Amman Institute of Technonology,Dept of Information Technology,Erode,Tamilnadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10616388/10616396/10616704.pdf?arnumber=10616704

Reference20 articles.

1. Pathobiomes Revealed that Pseudomonas fuscovaginae and Sarocladium oryzae Are Independently Associated with Rice Sheath Rot

2. Rice Leaf Diseases Recognition Using Convolutional Neural Networks

3. Rice diseases detection using Convolutional Neural Networks: A Survey

4. Plant Disease Detection and Classification by Deep Learning—A Review

5. Diagnosis of Alternaria disease and leafminer pest on tomato leaves using image processing techniques

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