Present and future scopes and challenges of plant pest and disease (P&D) monitoring: Remote sensing, image processing, and artificial intelligence perspectives-Reference-Cited by-同舟云学术

Present and future scopes and challenges of plant pest and disease (P&D) monitoring: Remote sensing, image processing, and artificial intelligence perspectives

Published:2023-11 Issue: Volume:32 Page:100996
ISSN:2352-9385
Container-title:Remote Sensing Applications: Society and Environment
language:en
Short-container-title:Remote Sensing Applications: Society and Environment

Author:

Abdullah Hasan M.^ORCID,Mohana Nusrat T.,Khan Bhoktear M.,Ahmed Syed M.,Hossain Maruf^ORCID,Islam KH Shakibul^ORCID,Redoy Mahadi H.^ORCID,Ferdush Jannatul,Bhuiyan M.A.H.B.^ORCID,Hossain Motaher M.,Ahamed Tofayel

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geography, Planning and Development

Reference143 articles.

1. Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review;Adam;Wetl. Ecol. Manag.,2010

2. Detection of charcoal rot (Macrophomina phaseolina) toxin effects in soybean (Glycine max) seedlings using hyperspectral spectroscopy;Al-Ahmadi;Comput. Electron. Agric.,2018

3. Multispectral band selection for imaging sensor design for vineyard disease detection: case of Flavescence Dorée;Al-Saddik;Adv. Anim. Biosci.,2017

4. Spectral characterization of bacterial leaf blight (BLB) of rice through spectroscopy and remotely sensed multi-spectral imagery;Alberto,2017

5. Fusion of drone-based RGB and multi-spectral imagery for shallow water bathymetry inversion;Alevizos;Rem. Sens.,2022

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing precision agriculture: A comprehensive review of machine learning and AI vision applications in all-terrain vehicle for farm automation;Smart Agricultural Technology;2024-08

2. Deep Learning-Based Detection of Foliar Diseases in Apple Plants Using an Assembled CNN Model;2024 Third International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN);2024-07-18

3. Machine Learning Algorithms for Predictive Pest Modeling;Advances in Environmental Engineering and Green Technologies;2024-06-28

4. Method for Monitoring Wheat Growth Status and Estimating Yield Based on UAV Multispectral Remote Sensing;Agronomy;2024-05-08

5. Utilizing convolutional neural networks (CNN) and U-Net architecture for precise crop and weed segmentation in agricultural imagery: A deep learning approach;Big Data Research;2024-05