Multimodal Hybrid Deep Learning Approach to Detect Tomato Leaf Disease Using Attention Based Dilated Convolution Feature Extractor with Logistic Regression Classification

Multimodal Hybrid Deep Learning Approach to Detect Tomato Leaf Disease Using Attention Based Dilated Convolution Feature Extractor with Logistic Regression Classification

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Automatic leaf disease detection techniques are effective for reducing the time-consuming effort of monitoring large crop farms and early identification of disease symptoms of plant leaves. Although crop tomatoes are seen to be susceptible to a variety of diseases that can reduce the production of t...

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Bibliographic Details
Main Authors: Md Shofiqul Islam, Sunjida Sultana, Fahmid Al Farid, Md Nahidul Islam, Mamunur Rashid, Bifta Sama Bari, Noramiza Hashim, Mohd Nizam Husen
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Sensors
Subjects:
dilated CNN
filtering
logistic regression
segmentation
tomato leaf disease
feature extraction
Online Access:https://www.mdpi.com/1424-8220/22/16/6079

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https://www.mdpi.com/1424-8220/22/16/6079

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