MPCSAR-AHH: A hybrid deep learning model for real-time detection of cassava leaf diseases and fertilizer recommendation-Reference-Cited by-同舟云学术

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MPCSAR-AHH: A hybrid deep learning model for real-time detection of cassava leaf diseases and fertilizer recommendation

Published:2024-11 Issue: Volume:119 Page:109628
ISSN:0045-7906
Container-title:Computers and Electrical Engineering
language:en
Short-container-title:Computers and Electrical Engineering

Author:

Prashanth J. Siva,Moparthi Nageswara Rao,Krishna G. Bala,Prasad A.V. Krishna,Sravankumar B.,Rao P. Ravinder

Publisher

Elsevier BV

Reference30 articles.

1. Deep neural network-based multi-class image classification for plant diseases;Negi;Agriculture,2021

2. A paradigm of internet-of-nano-things inspired intelligent plant pathogen-diagnostic biosensors;Sonu;ECS Sensors Plus,2022

3. FormerLeaf: An efficient vision transformer for cassava leaf disease detection;Thai;Comput Electron Agric,2023

4. FormerLeaf: An efficient vision transformer for cassava leaf disease detection;Kaur;Comput Electron Agric TURCOMAT,2021

5. EAPT: Efficient attention pyramid transformer for image processing;Lin;IEEE Trans Multimed,2021

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