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A Review on UAV-Based Applications for Plant Disease Detection and Monitoring

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/csc2.20623openalex-snapshot

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Recent advances in sensing plant diseases for precision crop protection

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Agricultural Innovation and the Role of Institutions: Lessons from the Game of Drones

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A low-cost UAV for detection of Cercospora leaf spot in okra using deep convolutional neural network

inferredcites →https://doi.org/10.1007/s11119-014-9360-yopenalex-snapshot

Detection of downy mildew of opium poppy using high-resolution multi-spectral and thermal imagery acquired with an unmanned aerial vehicle

inferredcites →https://doi.org/10.1007/s11119-019-09703-4openalex-snapshot

Detection of target spot and bacterial spot diseases in tomato using UAV-based and benchtop-based hyperspectral imaging techniques

inferredcites →https://doi.org/10.1007/s12038-021-00241-8openalex-snapshot

Different stages of disease detection in squash plant based on machine learning

inferredcites →https://doi.org/10.1007/s40858-021-00460-2openalex-snapshot

Identification of diseases and physiological disorders in potato via multispectral drone imagery using machine learning tools

inferredcites →https://doi.org/10.1007/s41324-019-00302-zopenalex-snapshot

Extraction of onion fields infected by anthracnose-twister disease in selected municipalities of Nueva Ecija using UAV imageries

inferredcites →https://doi.org/10.1007/s41348-019-00234-8openalex-snapshot

UAV-based multispectral imagery for fast Citrus Greening detection

inferredcites →https://doi.org/10.1016/j.agrformet.2020.108145openalex-snapshot

An Unmanned Aerial System (UAS) for concurrent measurements of solar-induced chlorophyll fluorescence and hyperspectral reflectance toward improving crop monitoring

inferredcites →https://doi.org/10.1016/j.biosystemseng.2016.01.017openalex-snapshot

A review on the main challenges in automatic plant disease identification based on visible range images

inferredcites →https://doi.org/10.1016/j.biosystemseng.2016.04.010openalex-snapshot

Field phenotyping system for the assessment of potato late blight resistance using RGB imagery from an unmanned aerial vehicle

inferredcites →https://doi.org/10.1016/j.biosystemseng.2018.05.013openalex-snapshot

Factors influencing the use of deep learning for plant disease recognition

inferredcites →https://doi.org/10.1016/j.biosystemseng.2020.02.016openalex-snapshot

The use of UAVs in monitoring yellow sigatoka in banana

inferredcites →https://doi.org/10.1016/j.compag.2018.10.006openalex-snapshot

Deep leaning approach with colorimetric spaces and vegetation indices for vine diseases detection in UAV images

inferredcites →https://doi.org/10.1016/j.compag.2018.10.017openalex-snapshot

Wheat yellow rust monitoring by learning from multispectral UAV aerial imagery

inferredcites →https://doi.org/10.1016/j.compag.2019.105035openalex-snapshot

Spatio-temporal monitoring of wheat yellow rust using UAV multispectral imagery

inferredcites →https://doi.org/10.1016/j.compag.2019.105147openalex-snapshot

Application of aerial remote sensing technology for detection of fire blight infected pear trees

inferredcites →https://doi.org/10.1016/j.compag.2020.105708openalex-snapshot

Early detection of bacterial wilt in peanut plants through leaf-level hyperspectral and unmanned aerial vehicle data

inferredcites →https://doi.org/10.1016/j.compag.2021.106033openalex-snapshot

A comprehensive review on recent applications of unmanned aerial vehicle remote sensing with various sensors for high-throughput plant phenotyping

inferredcites →https://doi.org/10.1016/j.compag.2021.106128openalex-snapshot

UAV-based high-throughput phenotyping to increase prediction and selection accuracy in maize varieties under artificial MSV inoculation

inferredcites →https://doi.org/10.1016/j.compag.2021.106298openalex-snapshot

Detection and mapping of trees infected with citrus gummosis using UAV hyperspectral data

inferredcites →https://doi.org/10.1016/j.compag.2021.106476openalex-snapshot

Detecting coffee leaf rust with UAV-based vegetation indices and decision tree machine learning models

inferredcites →https://doi.org/10.1016/j.compag.2022.107017openalex-snapshot

Drones in agriculture: A review and bibliometric analysis

inferredcites →https://doi.org/10.1016/j.compag.2022.107137openalex-snapshot

Remote sensing detection algorithm for apple fire blight based on UAV multispectral image

inferredcites →https://doi.org/10.1016/j.compag.2022.107211openalex-snapshot

Applying convolutional neural networks for detecting wheat stripe rust transmission centers under complex field conditions using RGB-based high spatial resolution images from UAVs

inferredcites →https://doi.org/10.1016/j.cropro.2014.12.008openalex-snapshot

Intercropping influenced the occurrence of stripe rust and powdery mildew in wheat

inferredcites →https://doi.org/10.1016/j.ejrs.2022.08.001openalex-snapshot

Predictive zoning of pest and disease infestations in rice field based on UAV aerial imagery

inferredcites →https://doi.org/10.1016/j.foreco.2018.11.032openalex-snapshot

Canopy temperature from an Unmanned Aerial Vehicle as an indicator of tree stress associated with red band needle blight severity

inferredcites →https://doi.org/10.1016/j.foreco.2021.118986openalex-snapshot

Application of conventional UAV-based high-throughput object detection to the early diagnosis of pine wilt disease by deep learning

inferredcites →https://doi.org/10.1016/j.iot.2020.100187openalex-snapshot

Internet of Things (IoT) and Agricultural Unmanned Aerial Vehicles (UAVs) in smart farming: A comprehensive review

inferredcites →https://doi.org/10.1016/j.isprsjprs.2020.08.025openalex-snapshot

Detection of banana plants and their major diseases through aerial images and machine learning methods: A case study in DR Congo and Republic of Benin

inferredcites →https://doi.org/10.1016/j.rse.2003.04.007openalex-snapshot

Remote sensing applications for precision agriculture: A learning community approach

inferredcites →https://doi.org/10.1016/j.rse.2013.07.031openalex-snapshot

High-resolution airborne hyperspectral and thermal imagery for early detection of Verticillium wilt of olive using fluorescence, temperature and narrow-band spectral indices

inferredcites →https://doi.org/10.1016/j.rse.2019.111599openalex-snapshot

Soybean yield prediction from UAV using multimodal data fusion and deep learning

inferredcites →https://doi.org/10.1016/j.scitotenv.2020.141814openalex-snapshot

A geostatistical fusion approach using UAV data for probabilistic estimation of Xylella fastidiosa subsp. pauca infection in olive trees

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Current progress in plant pathogen detection enabled by nanomaterials-based (bio)sensors

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UAV & satellite synergies for optical remote sensing applications: A literature review

inferredcites →https://doi.org/10.1016/j.suscom.2018.05.010openalex-snapshot

UAV based wilt detection system via convolutional neural networks

inferredcites →https://doi.org/10.1016/j.tplants.2018.11.007openalex-snapshot

Perspectives for Remote Sensing with Unmanned Aerial Vehicles in Precision Agriculture

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Opportunities and limitations for image-based remote sensing in precision crop management

inferredcites →https://doi.org/10.1038/s41558-021-01104-8openalex-snapshot

Plant pathogen infection risk tracks global crop yields under climate change

inferredcites →https://doi.org/10.1038/s41559-018-0793-yopenalex-snapshot

The global burden of pathogens and pests on major food crops

inferredcites →https://doi.org/10.1073/pnas.2022239118openalex-snapshot

The persistent threat of emerging plant disease pandemics to global food security

inferredcites →https://doi.org/10.1080/03075079.2014.914907openalex-snapshot

Publishing not perishing: how research students transition from novice to knowledgeable using systematic quantitative literature reviews

inferredcites →https://doi.org/10.1080/07038992.2021.1971960openalex-snapshot

Detection of Lesions in Lettuce Caused by Pectobacterium carotovorum Subsp. carotovorum by Supervised Classification Using Multispectral Images

inferredcites →https://doi.org/10.1080/07294360.2013.841651openalex-snapshot

The benefits of publishing systematic quantitative literature reviews for PhD candidates and other early-career researchers

inferredcites →https://doi.org/10.1080/07352681003617285openalex-snapshot

Plant Disease Severity Estimated Visually, by Digital Photography and Image Analysis, and by Hyperspectral Imaging

inferredcites →https://doi.org/10.1080/22797254.2019.1642143openalex-snapshot

Aerial multispectral imagery for plant disease detection: radiometric calibration necessity assessment

inferredcites →https://doi.org/10.1093/gigascience/giac054openalex-snapshot

Agricultural plant cataloging and establishment of a data framework from UAV-based crop images by computer vision

inferredcites →https://doi.org/10.1094/pdis-03-15-0340-feopenalex-snapshot

Plant Disease Detection by Imaging Sensors – Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping

inferredcites →https://doi.org/10.1094/pdis-08-18-1373-reopenalex-snapshot

An Improved Crop Scouting Technique Incorporating Unmanned Aerial Vehicle–Assisted Multispectral Crop Imaging into Conventional Scouting Practice for Gummy Stem Blight in Watermelon

inferredcites →https://doi.org/10.1094/pdis-12-17-1893-reopenalex-snapshot

Detecting Wheat Powdery Mildew and Predicting Grain Yield Using Unmanned Aerial Photography

inferredcites →https://doi.org/10.1094/pdis.2000.84.8.816openalex-snapshot

Regional Monitoring for Disease Prediction and Optimization of Plant Protection Measuares: The IPM Wheat Model

inferredcites →https://doi.org/10.1109/access.2021.3073929openalex-snapshot

A Remote Sensing and Airborne Edge-Computing Based Detection System for Pine Wilt Disease

inferredcites →https://doi.org/10.1109/jsen.2021.3064060openalex-snapshot

Notice of Violation of IEEE Publication Principles: Grape Disease Detection Network Based on Multi-Task Learning and Attention Features

inferredcites →https://doi.org/10.1109/jsen.2022.3156097openalex-snapshot

Wheat Yellow Rust Severity Detection by Efficient DF-UNet and UAV Multispectral Imagery

inferredcites →https://doi.org/10.1109/lgrs.2017.2743715openalex-snapshot

Identification of Soybean Foliar Diseases Using Unmanned Aerial Vehicle Images

inferredcites →https://doi.org/10.1109/lgrs.2019.2932385openalex-snapshot

Automatic Recognition of Soybean Leaf Diseases Using UAV Images and Deep Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/tii.2020.2979237openalex-snapshot

Aerial Visual Perception in Smart Farming: Field Study of Wheat Yellow Rust Monitoring

inferredcites →https://doi.org/10.1111/j.1365-3059.2010.02411.xopenalex-snapshot

Climate change, plant diseases and food security: an overview

inferredcites →https://doi.org/10.1111/ppa.12842openalex-snapshot

Using image analysis for quantitative assessment of needle bladder rust disease of Norway spruce

inferredcites →https://doi.org/10.1136/bmj.b2535openalex-snapshot

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

inferredcites →https://doi.org/10.1146/annurev-virology-092818-015606openalex-snapshot

Global Dimensions of Plant Virus Diseases: Current Status and Future Perspectives

inferredcites →https://doi.org/10.1146/annurev.phyto.40.021202.110417openalex-snapshot

E VOLUTIONARY E COLOGY OF P LANT D ISEASES IN N ATURAL E COSYSTEMS

inferredcites →https://doi.org/10.1186/s40663-021-00328-6openalex-snapshot

Early detection of pine wilt disease in Pinus tabuliformis in North China using a field portable spectrometer and UAV-based hyperspectral imagery

inferredcites →https://doi.org/10.1371/journal.pone.0187470openalex-snapshot

Detection of rice sheath blight using an unmanned aerial system with high-resolution color and multispectral imaging

inferredcites →https://doi.org/10.14601/phytopathol_mediterr-18312openalex-snapshot

Unmanned Aerial Vehicle (UAV)-based remote sensing to monitor grapevine leaf stripe disease within a vineyard affected by esca complex

inferredcites →https://doi.org/10.18280/jesa.530115openalex-snapshot

Diseased Area Recognition and Pesticide Spraying in Farming Lands by Multicopters and Image Processing System

inferredcites →https://doi.org/10.2135/tppj2019.03.0006openalex-snapshot

Autonomous Detection of Plant Disease Symptoms Directly from Aerial Imagery

inferredcites →https://doi.org/10.21894/jopr.2020.0035openalex-snapshot

ANALYSIS OF MULTISPECTRAL IMAGERY FROM UNMANNED AERIAL VEHICLE (UAV) USING OBJECT-BASED IMAGE ANALYSIS FOR DETECTION OF Ganoderma DISEASE IN OIL PALM

inferredcites →https://doi.org/10.25165/j.ijabe.20201303.5524openalex-snapshot

Identification of banana fusarium wilt using supervised classification algorithms with UAV-based multi-spectral imagery

inferredcites →https://doi.org/10.3389/fpls.2019.01550openalex-snapshot

Millimeter-Level Plant Disease Detection From Aerial Photographs via Deep Learning and Crowdsourced Data

inferredcites →https://doi.org/10.3389/fpls.2021.628575openalex-snapshot

UAV-Based Thermal, RGB Imaging and Gene Expression Analysis Allowed Detection of Fusarium Head Blight and Gave New Insights Into the Physiological Responses to the Disease in Durum Wheat

inferredcites →https://doi.org/10.3389/fpls.2022.1000093openalex-snapshot

Early detection of pine wilt disease tree candidates using time-series of spectral signatures

inferredcites →https://doi.org/10.3389/fpls.2022.1004427openalex-snapshot

Detection of wheat Fusarium head blight using UAV-based spectral and image feature fusion

inferredcites →https://doi.org/10.3389/fpls.2022.791018openalex-snapshot

Identification and Classification of Downy Mildew Severity Stages in Watermelon Utilizing Aerial and Ground Remote Sensing and Machine Learning

inferredcites →https://doi.org/10.3389/fpls.2022.949054openalex-snapshot

The Stress Detection and Segmentation Strategy in Tea Plant at Canopy Level

inferredcites →https://doi.org/10.3390/agriculture11080707openalex-snapshot

Review on Convolutional Neural Network (CNN) Applied to Plant Leaf Disease Classification

inferredcites →https://doi.org/10.3390/agronomy12092000openalex-snapshot

Protective Effects of Systiva® Seed Treatment Fungicide for the Control of Winter Wheat Foliar Diseases Caused at Early Stages Due to Climate Change

inferredcites →https://doi.org/10.3390/agronomy12122911openalex-snapshot

Early Detection of Coffee Leaf Rust Caused by Hemileia vastatrix Using Multispectral Images

inferredcites →https://doi.org/10.3390/app122010278openalex-snapshot

MobiRes-Net: A Hybrid Deep Learning Model for Detecting and Classifying Olive Leaf Diseases

inferredcites →https://doi.org/10.3390/biology11121732openalex-snapshot

Artificial Intelligence-Based Robust Hybrid Algorithm Design and Implementation for Real-Time Detection of Plant Diseases in Agricultural Environments

inferredcites →https://doi.org/10.3390/drones3020040openalex-snapshot

A Review on the Use of Unmanned Aerial Vehicles and Imaging Sensors for Monitoring and Assessing Plant Stresses

inferredcites →https://doi.org/10.3390/drones4030041openalex-snapshot

A Review on Drone-Based Data Solutions for Cereal Crops

inferredcites →https://doi.org/10.3390/drones5020034openalex-snapshot

UAV-Based Classification of Cercospora Leaf Spot Using RGB Images

inferredcites →https://doi.org/10.3390/drones6090230openalex-snapshot

Detection of White Leaf Disease in Sugarcane Using Machine Learning Techniques over UAV Multispectral Images

inferredcites →https://doi.org/10.3390/f12101393openalex-snapshot

Early Monitoring of Health Status of Plantation-Grown Eucalyptus pellita at Large Spatial Scale via Visible Spectrum Imaging of Canopy Foliage Using Unmanned Aerial Vehicles

inferredcites →https://doi.org/10.3390/land10020164openalex-snapshot

Exploring the Challenges Posed by Regulations for the Use of Drones in Agriculture in the African Context

inferredcites →https://doi.org/10.3390/plants10122726openalex-snapshot

Sustainability Trait Modeling of Field-Grown Switchgrass (Panicum virgatum) Using UAV-Based Imagery

inferredcites →https://doi.org/10.3390/rs10050787openalex-snapshot

Aerial and Ground Based Sensing of Tolerance to Beet Cyst Nematode in Sugar Beet

inferredcites →https://doi.org/10.3390/rs10101513openalex-snapshot

Evaluating Late Blight Severity in Potato Crops Using Unmanned Aerial Vehicles and Machine Learning Algorithms

inferredcites →https://doi.org/10.3390/rs11030224openalex-snapshot

Feasibility of Unmanned Aerial Vehicle Optical Imagery for Early Detection and Severity Assessment of Late Blight in Potato

inferredcites →https://doi.org/10.3390/rs11111373openalex-snapshot

UAV-Based Remote Sensing Technique to Detect Citrus Canker Disease Utilizing Hyperspectral Imaging and Machine Learning

inferredcites →https://doi.org/10.3390/rs11131554openalex-snapshot

A Deep Learning-Based Approach for Automated Yellow Rust Disease Detection from High-Resolution Hyperspectral UAV Images

inferredcites →https://doi.org/10.3390/rs11192209openalex-snapshot

Quantitative Phenotyping of Northern Leaf Blight in UAV Images Using Deep Learning

inferredcites →https://doi.org/10.3390/rs11212495openalex-snapshot

In-Field Detection of Yellow Rust in Wheat on the Ground Canopy and UAV Scale

inferredcites →https://doi.org/10.3390/rs12010170openalex-snapshot

Quantifying Citrus Tree Health Using True Color UAV Images

inferredcites →https://doi.org/10.3390/rs12060938openalex-snapshot

Recognition of Banana Fusarium Wilt Based on UAV Remote Sensing

inferredcites →https://doi.org/10.3390/rs12081310openalex-snapshot

Automatic Classification of Cotton Root Rot Disease Based on UAV Remote Sensing

inferredcites →https://doi.org/10.3390/rs12091357openalex-snapshot

Crop Monitoring Using Satellite/UAV Data Fusion and Machine Learning

inferredcites →https://doi.org/10.3390/rs12091491openalex-snapshot

Applications of UAV Thermal Imagery in Precision Agriculture: State of the Art and Future Research Outlook

inferredcites →https://doi.org/10.3390/rs12142194openalex-snapshot

Prediction of the Kiwifruit Decline Syndrome in Diseased Orchards by Remote Sensing

inferredcites →https://doi.org/10.3390/rs12152445openalex-snapshot

UAV-Based Multispectral Phenotyping for Disease Resistance to Accelerate Crop Improvement under Changing Climate Conditions

inferredcites →https://doi.org/10.3390/rs12152453openalex-snapshot

A Plant-by-Plant Method to Identify and Treat Cotton Root Rot Based on UAV Remote Sensing

inferredcites →https://doi.org/10.3390/rs12172678openalex-snapshot

Detection of Citrus Huanglongbing Based on Multi-Input Neural Network Model of UAV Hyperspectral Remote Sensing

inferredcites →https://doi.org/10.3390/rs12172732openalex-snapshot

Laboratory and UAV-Based Identification and Classification of Tomato Yellow Leaf Curl, Bacterial Spot, and Target Spot Diseases in Tomato Utilizing Hyperspectral Imaging and Machine Learning

inferredcites →https://doi.org/10.3390/rs12172863openalex-snapshot

Fusarium Wilt of Radish Detection Using RGB and Near Infrared Images from Unmanned Aerial Vehicles

inferredcites →https://doi.org/10.3390/rs12203305openalex-snapshot

VddNet: Vine Disease Detection Network Based on Multispectral Images and Depth Map

inferredcites →https://doi.org/10.3390/rs12223696openalex-snapshot

Monitoring Wheat Leaf Rust and Stripe Rust in Winter Wheat Using High-Resolution UAV-Based Red-Green-Blue Imagery

inferredcites →https://doi.org/10.3390/rs13010123openalex-snapshot

Wheat Yellow Rust Detection Using UAV-Based Hyperspectral Technology

inferredcites →https://doi.org/10.3390/rs13132567openalex-snapshot

Tar Spot Disease Quantification Using Unmanned Aircraft Systems (UAS) Data

inferredcites →https://doi.org/10.3390/rs13193841openalex-snapshot

Automatic Identification and Monitoring of Plant Diseases Using Unmanned Aerial Vehicles: A Review

inferredcites →https://doi.org/10.3390/rs13224562openalex-snapshot

Remote Sensing Detecting of Yellow Leaf Disease of Arecanut Based on UAV Multisource Sensors

inferredcites →https://doi.org/10.3390/rs14020293openalex-snapshot

Human vs. Machine, the Eyes Have It. Assessment of Stemphylium Leaf Blight on Onion Using Aerial Photographs from an NIR Camera

inferredcites →https://doi.org/10.3390/rs14020396openalex-snapshot

Novel CropdocNet Model for Automated Potato Late Blight Disease Detection from Unmanned Aerial Vehicle-Based Hyperspectral Imagery

inferredcites →https://doi.org/10.3390/rs14030799openalex-snapshot

Early Detection of Basal Stem Rot Disease in Oil Palm Tree Using Unmanned Aerial Vehicle-Based Hyperspectral Imaging

inferredcites →https://doi.org/10.3390/rs14051231openalex-snapshot

Banana Fusarium Wilt Disease Detection by Supervised and Unsupervised Methods from UAV-Based Multispectral Imagery

inferredcites →https://doi.org/10.3390/rs14051239openalex-snapshot

Unmanned Aerial Vehicle (UAV)-Based Remote Sensing for Early-Stage Detection of Ganoderma

inferredcites →https://doi.org/10.3390/rs14112551openalex-snapshot

Classification of Southern Corn Rust Severity Based on Leaf-Level Hyperspectral Data Collected under Solar Illumination

inferredcites →https://doi.org/10.3390/rs14194765openalex-snapshot

A Two-Step Machine Learning Approach for Crop Disease Detection Using GAN and UAV Technology

inferredcites →https://doi.org/10.3390/rs14205206openalex-snapshot

Banana Mapping in Heterogenous Smallholder Farming Systems Using High-Resolution Remote Sensing Imagery and Machine Learning Models with Implications for Banana Bunchy Top Disease Surveillance

inferredcites →https://doi.org/10.3390/rs14236031openalex-snapshot

Plant Disease Diagnosis Using Deep Learning Based on Aerial Hyperspectral Images: A Review

inferredcites →https://doi.org/10.3390/rs14246232openalex-snapshot

Ultra-High-Resolution UAV-Based Detection of Alternaria solani Infections in Potato Fields

inferredcites →https://doi.org/10.3390/rs15092450openalex-snapshot

Recent Advances in Crop Disease Detection Using UAV and Deep Learning Techniques

inferredcites →https://doi.org/10.3390/rs9040308openalex-snapshot

Detection of Flavescence dorée Grapevine Disease Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery

inferredcites →https://doi.org/10.3390/s17112557openalex-snapshot

Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture

inferredcites →https://doi.org/10.3390/s18040944openalex-snapshot

Aerial Mapping of Forests Affected by Pathogens Using UAVs, Hyperspectral Sensors, and Artificial Intelligence

inferredcites →https://doi.org/10.3390/s18124464openalex-snapshot

Fast Detection of Sclerotinia Sclerotiorum on Oilseed Rape Leaves Using Low-Altitude Remote Sensing Technology

inferredcites →https://doi.org/10.3390/s19245477openalex-snapshot

Object-Based Image Analysis Applied to Low Altitude Aerial Imagery for Potato Plant Trait Retrieval and Pathogen Detection

inferredcites →https://doi.org/10.3390/s20174915openalex-snapshot

Fast Detection of Olive Trees Affected by Xylella Fastidiosa from UAVs Using Multispectral Imaging

inferredcites →https://doi.org/10.3390/s21196540openalex-snapshot

A Deep-Learning-Based Approach for Wheat Yellow Rust Disease Recognition from Unmanned Aerial Vehicle Images

inferredcites →https://doi.org/10.34133/2020/9452123openalex-snapshot

Scoring Cercospora Leaf Spot on Sugar Beet: Comparison of UGV and UAV Phenotyping Systems

inferredcites →https://doi.org/10.36961/si28345openalex-snapshot

Sensing the occurrence and dynamics of Cercospora leaf spot disease using UAV-supported image data and deep learning

inferredcites →https://doi.org/10.46488/nept.2022.v21i02.053openalex-snapshot

An Improved Convolutional Neural Network for Plant Disease Detection Using Unmanned Aerial Vehicle Images

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.3897/ved.197154zenodo-depositor-declared

UAV-based RGB imagery for assessing vegetation status in a Mediterranean area affected by Xylella fastidiosa

inferred← citeshttps://doi.org/10.1002/agg2.70201openalex-snapshot

Assessment of beet leaf yellowing virus tolerance based on leaf yellowing in sugar beet

inferred← citeshttps://doi.org/10.1002/cem.3603openalex-snapshot

Next‐Gen Crop Monitoring: MTEG‐RTU Algorithm and UAV Synergy for Precise Disease Diagnosis

inferred← citeshttps://doi.org/10.1002/csc2.70202openalex-snapshot

Breeding for quantitative disease resistance: Case studies, emerging approaches, and exploiting pathogen variation

inferred← citeshttps://doi.org/10.1007/978-3-031-87035-4_32openalex-snapshot

Innovative Technologies for Surveillance and Management of Mango Tree Diseases and Disorders in a Changing Climate

inferred← citeshttps://doi.org/10.1007/978-3-031-99954-3_5openalex-snapshot

High-Throughput Phenotyping in Wheat

inferred← citeshttps://doi.org/10.1007/978-3-032-05603-0_13openalex-snapshot

IOT and UAV Integrated System for Proactive Crop Disease Prediction

inferred← citeshttps://doi.org/10.1007/978-981-95-3483-8_14openalex-snapshot

A Survey on Crop Disease Prediction Detection: AI Models Trained on Multispectral and Hyperspectral Images for Early Disease Detection

inferred← citeshttps://doi.org/10.1007/978-981-96-8402-1_8openalex-snapshot

Technological Advances in UAV-Assisted Crop Monitoring

inferred← citeshttps://doi.org/10.1007/978-981-96-9935-3_28openalex-snapshot

Enhancing Accuracy of Corn Leaf Disease Detection: Machine Learning Approach

inferred← citeshttps://doi.org/10.1007/s10462-025-11234-6openalex-snapshot

Plant leaf disease detection and classification using convolution neural networks model: a review

inferred← citeshttps://doi.org/10.1007/s11557-026-02122-6openalex-snapshot

A preliminary assessment of ATR-FTIR imaging for detecting and mapping Corinectria constricta in Pinus radiata wood in Chile

inferred← citeshttps://doi.org/10.1007/s12230-026-10057-7openalex-snapshot

UAV-Based Multi-Feature Machine Learning Framework for Early Blight (Alternaria solani) Detection and Precision Spray Zoning in Potato

inferred← citeshttps://doi.org/10.1007/s41870-025-03048-0openalex-snapshot

AI-driven precision farming: UAV-based multispectral and CNN framework for tea leaf disease detection

inferred← citeshttps://doi.org/10.1007/s43621-024-00736-yopenalex-snapshot

Future of sustainable farming: exploring opportunities and overcoming barriers in drone-IoT integration

inferred← citeshttps://doi.org/10.1007/s44163-026-00973-2openalex-snapshot

A systematic review of deep learning and super resolution techniques for leaf level and canopy level plant disease detection

inferred← citeshttps://doi.org/10.1007/s44279-026-00627-yopenalex-snapshot

Remote sensing applications for Lettuce (Lactuca sativa L) across field and controlled environments: a review

inferred← citeshttps://doi.org/10.1007/s44447-026-00186-0openalex-snapshot

HYRNet- hybrid yellow rust stage-aware severity classification XAI enabled deep learning framework

inferred← citeshttps://doi.org/10.1016/bs.agron.2025.10.005openalex-snapshot

Operational and analytical frameworks of Unoccupied Aerial Vehicles (UAV) for precision agriculture applications

inferred← citeshttps://doi.org/10.1016/j.aca.2024.343153openalex-snapshot

A new framework for interval wavelength selection based on wavelength importance clustering

inferred← citeshttps://doi.org/10.1016/j.aiia.2026.04.008openalex-snapshot

From plots to region: Machine learning-based UAV-satellite integration for mapping fractional coverage of peanut southern blight

inferred← citeshttps://doi.org/10.1016/j.atech.2024.100740openalex-snapshot

Configuration of a multisensor platform for advanced plant phenotyping and disease detection: Case study on Cercospora leaf spot in sugar beet

inferred← citeshttps://doi.org/10.1016/j.atech.2025.101047openalex-snapshot

BFWSD: A lightweight algorithm for banana fusarium wilt severity detection via UAV-Based Large-Scale Monitoring

inferred← citeshttps://doi.org/10.1016/j.atech.2025.101075openalex-snapshot

Adaptive path planning for efficient object search by UAVs in agricultural fields

inferred← citeshttps://doi.org/10.1016/j.atech.2025.101406openalex-snapshot

A review of the application of UAV multispectral remote sensing technology in precision agriculture

inferred← citeshttps://doi.org/10.1016/j.atech.2025.101452openalex-snapshot

Reliable NDVI estimation in wheat using low-Cost UAV-derived RGB vegetation indices

inferred← citeshttps://doi.org/10.1016/j.atech.2025.101729openalex-snapshot

Estimating wheat disease severity from high-resolution UAV multispectral imagery using deep learning

inferred← citeshttps://doi.org/10.1016/j.atech.2026.102200openalex-snapshot

YOLOKIWI: A kiwifruit sunburn monitoring model integrating adaptive features

inferred← citeshttps://doi.org/10.1016/j.clcb.2024.100132openalex-snapshot

The digital future of farming: A bibliometric analysis of big data in smart farming research

inferred← citeshttps://doi.org/10.1016/j.compag.2024.109089openalex-snapshot

ISMSFuse: Multi-modal fusing recognition algorithm for rice bacterial blight disease adaptable in edge computing scenarios

inferred← citeshttps://doi.org/10.1016/j.compag.2024.109158openalex-snapshot

Detection and monitoring wheat diseases using unmanned aerial vehicles (UAVs)

inferred← citeshttps://doi.org/10.1016/j.compag.2024.109656openalex-snapshot

Aquatic plants detection in crab ponds using UAV hyperspectral imagery combined with transformer-based semantic segmentation model

inferred← citeshttps://doi.org/10.1016/j.compag.2025.109927openalex-snapshot

EF-CenterNet: An efficient anchor-free model for UAV-based banana leaf disease detection

inferred← citeshttps://doi.org/10.1016/j.compag.2025.110597openalex-snapshot

Multiscale phenotyping of grain crops based on three-dimensional models: A comprehensive review of trait detection

inferred← citeshttps://doi.org/10.1016/j.compag.2025.110679openalex-snapshot

The application of UAV technology in maize crop protection strategies: A review

inferred← citeshttps://doi.org/10.1016/j.compag.2025.111322openalex-snapshot

SPVD-DETR: A novel real-time end-to-end object detector of sweetpotato virus disease from unmanned aerial vehicle ortho imagery

inferred← citeshttps://doi.org/10.1016/j.compag.2026.111426openalex-snapshot

UAV remote sensing-driven precision variable management in cotton: technological framework, applications, and research outlook

inferred← citeshttps://doi.org/10.1016/j.compag.2026.112391openalex-snapshot

Coupling leaf electrical impedance spectroscopy with defense-hormone dynamics for pre-symptomatic rice blast detection

inferred← citeshttps://doi.org/10.1016/j.ecoinf.2025.103210openalex-snapshot

A novel method for monitoring Cladophora blooms in Qinghai Lake based on UAV imagery

inferred← citeshttps://doi.org/10.1016/j.hybadv.2025.100440openalex-snapshot

Comparative result analysis of cauliflower disease classification based on deep learning approach VGG16, inception v3, ResNet, and a custom CNN model

inferred← citeshttps://doi.org/10.1016/j.measurement.2026.122088openalex-snapshot

Latent-stage and real-time detection of maize rust: a portable device integrating snapshot spectral imaging and optimized deep learning

inferred← citeshttps://doi.org/10.1016/j.optlaseng.2025.109496openalex-snapshot

Wide-field high-resolution anamorphic Scheimpflug LiDAR for 3D plant fluorescence imaging

inferred← citeshttps://doi.org/10.1016/j.rsase.2025.101717openalex-snapshot

Acquisition of oilseed rape seedling population based on visible light imagery from unmanned aerial vehicles

inferred← citeshttps://doi.org/10.1021/acsagscitech.5c00197openalex-snapshot

Advancing Diagnostics for Xanthomonas oryzae pv. oryzae : Challenges and Future Directions

inferred← citeshttps://doi.org/10.1088/2515-7620/ae85e2openalex-snapshot

Canopy-normalized UAV measurement of fungicide efficacy in wheat rust: revealing treatment-induced bias in disease observability

inferred← citeshttps://doi.org/10.1088/2631-8695/adfcb2openalex-snapshot

A DTW-based feature extraction method for frequency-hopping signal classification with data-optimized CNN

inferred← citeshttps://doi.org/10.1094/phyto-11-24-0359-fiopenalex-snapshot

Opportunities and Challenges in Combining Optical Sensing and Epidemiological Modeling

inferred← citeshttps://doi.org/10.1109/accai61061.2024.10602232openalex-snapshot

Automatic Classification of Plant Leaf Images into Healthy and Disease Class with EfficientNet: A Study

inferred← citeshttps://doi.org/10.1109/access.2024.3449895openalex-snapshot

Path Planning and Trajectory Tracking Control of Quadrotor Dragging System in Marine Environment

inferred← citeshttps://doi.org/10.1109/access.2024.3488751openalex-snapshot

Optimal Fuzzy Deep Neural Networks-Based Plant Disease Detection and Classification on UAV-Based Remote Sensed Data

inferred← citeshttps://doi.org/10.1109/acmlc70381.2026.11700467openalex-snapshot

An AI-Driven Drone Imaging Framework for Precision Corn Disease Detection and Field Analytics

inferred← citeshttps://doi.org/10.1109/icac61394.2024.10718773openalex-snapshot

UAV and AI-Driven Approaches for Accurate Species Classification in Railway Trackside Vegetation Management

inferred← citeshttps://doi.org/10.1109/icbds67396.2025.11377223openalex-snapshot

Predictive Crop Health Analytics via Sensor Fusion: Integrating Soil IoT, UAV Multispectral Data, and Machine Learning

inferred← citeshttps://doi.org/10.1109/iccc65605.2025.11022835openalex-snapshot

A YOLO-Based Approach for Detection of Olive Knot Disease through UAV and Computer Vision Technologies

inferred← citeshttps://doi.org/10.1109/icccn61486.2024.10637527openalex-snapshot

iCrop: Enabling High-Precision Crop Disease Detection via LoRa Technology

inferred← citeshttps://doi.org/10.1109/iccsp64183.2025.11088677openalex-snapshot

UAV Based Maize Crop Images Classification as Leaf and Soil Using Color Space and Machine Learning Models

inferred← citeshttps://doi.org/10.1109/icdsns62112.2024.10690870openalex-snapshot

Automated Detection and Alerting System for Wheat Leaf Diseases Using the VGG16 Deep Learning Model

inferred← citeshttps://doi.org/10.1109/iementech202669403.2026.11434266openalex-snapshot

Hybrid Edge AI and Laser Triangulation Framework for Offline Plant Disease Detection in Resource Constrained Environments*

inferred← citeshttps://doi.org/10.1109/ietc69527.2026.11568646openalex-snapshot

Machine Learning-Based Instance Segmentation of Potato Virus Y (PVY) Symptoms in Seed Potato Crops Using RGB Imagery

inferred← citeshttps://doi.org/10.1109/wf-iot62078.2024.10811379openalex-snapshot

IoT and UAV imaging for indoor plant disease detection

inferred← citeshttps://doi.org/10.1142/s0218194025500913openalex-snapshot

Adaptive Fine-Grained Attention and Multi-Scale Fusion Mechanism for Real-Time Small Traffic Object Detection

inferred← citeshttps://doi.org/10.15507/2658-4123.036.202601.114-139openalex-snapshot

Development of a Low-Power Onboard System for Spot Detection of Wheat Phytopathologies Using a Modified YOLO Architecture

inferred← citeshttps://doi.org/10.21203/rs.3.rs-11111373/v1openalex-snapshot

PCR-Validated Comparative Deep Learning Analysis of CNN and YOLO Models for UAV-Based multi-spectral Detection of Sugarcane White Leaf Disease (WLD)

inferred← citeshttps://doi.org/10.21203/rs.3.rs-9668241/v1openalex-snapshot

Spatio-Temporal Data Fusion for Early Detection of Phytophthora cinnamomi in Macadamia Orchards using UAV-LiDAR and Multispectral Imagery

inferred← citeshttps://doi.org/10.2139/ssrn.4838597openalex-snapshot

Recent Advancements and Challenges in Deep Learning and Internet of Things for Precision Agriculture

inferred← citeshttps://doi.org/10.22314/2073-7599-2025-19-1-86-95openalex-snapshot

Major Trends in the Development of Aerial Photography Technology for Agricultural Lands

inferred← citeshttps://doi.org/10.26898/0370-8799-2025-10-10openalex-snapshot

Plant disease diagnostics using an unmanned aerial vehicle with low-power computing modules

inferred← citeshttps://doi.org/10.26898/0370-8799-2025-8-1openalex-snapshot

Application of ResNet for identification of weeds in grain crops

inferred← citeshttps://doi.org/10.31677/2072-6724-2025-76-3-158-167openalex-snapshot

Deep learning for automated weed monitoring in grain crops

inferred← citeshttps://doi.org/10.3389/fpls.2025.1633206openalex-snapshot

Spatiotemporal pattern analysis of juglans leaf necrosis disease occurrence and development in southern Xinjiang, China, based on UAV

inferred← citeshttps://doi.org/10.3390/agriculture14111876openalex-snapshot

Using UAV Images and Phenotypic Traits to Predict Potato Morphology and Yield in Peru

inferred← citeshttps://doi.org/10.3390/agriengineering7040120openalex-snapshot

Tomato Leaf Detection, Segmentation, and Extraction in Real-Time Environment for Accurate Disease Detection

inferred← citeshttps://doi.org/10.3390/agriengineering7120397openalex-snapshot

Economic Impact of Optical Sensors and Deep Learning in Smart Agriculture: A Scientometric Analysis

inferred← citeshttps://doi.org/10.3390/agriengineering8010022openalex-snapshot

Remote Sensing of Nematode Stress in Coffee: UAV-Based Multispectral and Thermal Imaging Approaches

inferred← citeshttps://doi.org/10.3390/agriengineering8030115openalex-snapshot

Implementation of a Scalable Aerial Crop Monitoring System for Educational Purposes (ACMS-E): The Case of Emerging Markets

inferred← citeshttps://doi.org/10.3390/agriengineering8080340openalex-snapshot

Spatial Mapping of Avocado Anthracnose Severity Using UAV-Derived Vegetation Indices in Amazonas, Peru

inferred← citeshttps://doi.org/10.3390/agronomy13112801openalex-snapshot

Feasibility of Detecting Sweet Potato (Ipomoea batatas) Virus Disease from High-Resolution Imagery in the Field Using a Deep Learning Framework

inferred← citeshttps://doi.org/10.3390/app14188339openalex-snapshot

Online Trajectory Replanning for Avoiding Moving Obstacles Using Fusion Prediction and Gradient-Based Optimization

inferred← citeshttps://doi.org/10.3390/app15137317openalex-snapshot

MSFNet: A Multi-Source Fusion-Based Method with Enhanced Hierarchical Spectral Semantic Perception for Wheat Disease Region Classification

inferred← citeshttps://doi.org/10.3390/drones10040235openalex-snapshot

A Plant-Level Survival Modeling Framework for Spatiotemporal Strawberry Canopy Decline Using UAV Multispectral Time Series

inferred← citeshttps://doi.org/10.3390/drones8110664openalex-snapshot

Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture

inferred← citeshttps://doi.org/10.3390/drones9120865openalex-snapshot

Application of UAVs and Machine Learning Methods for Mapping and Assessing Salinity in Agricultural Fields in Southern Kazakhstan

inferred← citeshttps://doi.org/10.3390/electronics13234715openalex-snapshot

Customized Weighted Ensemble of Modified Transfer Learning Models for the Detection of Sugarcane Leaf Diseases

inferred← citeshttps://doi.org/10.3390/f15081309openalex-snapshot

Detection Model and Spectral Disease Indices for Poplar (Populus L.) Anthracnose Based on Hyperspectral Reflectance

inferred← citeshttps://doi.org/10.3390/info17060529openalex-snapshot

An Automated Information Processing Framework for UAV-Based Detection and Spatial Mapping of Crop Damage Using Deep Learning

inferred← citeshttps://doi.org/10.3390/jmse13081537openalex-snapshot

A Study on UAV Path Planning for Navigation Mark Inspection Using Two Improved SOM Algorithms

inferred← citeshttps://doi.org/10.3390/pathogens13100904openalex-snapshot

Visually Asymptomatic Leaf Loss in Xylella fastidiosa-Infected Blueberry Plants

inferred← citeshttps://doi.org/10.3390/resources14100152openalex-snapshot

Agroforestry as a Resource for Resilience in the Technological Era: The Case of Ukraine

inferred← citeshttps://doi.org/10.3390/rs16163046openalex-snapshot

GVC-YOLO: A Lightweight Real-Time Detection Method for Cotton Aphid-Damaged Leaves Based on Edge Computing

inferred← citeshttps://doi.org/10.3390/rs17040698openalex-snapshot

Advances in Deep Learning Applications for Plant Disease and Pest Detection: A Review

inferred← citeshttps://doi.org/10.3390/rs17142388openalex-snapshot

Unmanned Aerial Vehicle-Based RGB Imaging and Lightweight Deep Learning for Downy Mildew Detection in Kimchi Cabbage

inferred← citeshttps://doi.org/10.3390/rs17162799openalex-snapshot

High-Throughput UAV Hyperspectral Remote Sensing Pinpoints Bacterial Leaf Streak Resistance in Wheat

inferred← citeshttps://doi.org/10.3390/rs18111769openalex-snapshot

UAV RGB Imagery as an Early-Warning Tool of Wheat Rust Pathogen-Induced Physiological Changes

inferred← citeshttps://doi.org/10.3390/rs18162806openalex-snapshot

A Hex-View Perspective on Plant Disease Detection Using Remote Sensing

inferred← citeshttps://doi.org/10.3390/s23239541openalex-snapshot

Multi-Objective Optimization in Air-to-Air Communication System Based on Multi-Agent Deep Reinforcement Learning

inferred← citeshttps://doi.org/10.3390/s24103153openalex-snapshot

DMAF-NET: Deep Multi-Scale Attention Fusion Network for Hyperspectral Image Classification with Limited Samples

inferred← citeshttps://doi.org/10.3390/s24248172openalex-snapshot

A Systematic Review on the Advancements in Remote Sensing and Proximity Tools for Grapevine Disease Detection

inferred← citeshttps://doi.org/10.3390/s25020479openalex-snapshot

An Over-Actuated Hexacopter Tilt-Rotor UAV Prototype for Agriculture of Precision: Modeling and Control

inferred← citeshttps://doi.org/10.3390/s25154876openalex-snapshot

A Review of Indian-Based Drones in the Agriculture Sector: Issues, Challenges, and Solutions

inferred← citeshttps://doi.org/10.3390/s26020374openalex-snapshot

Direct UAV-Based Detection of Botrytis cinerea in Vineyards Using Chlorophyll-Absorption Indices and YOLO Deep Learning

inferred← citeshttps://doi.org/10.3390/s26082465openalex-snapshot

Remote Sensing Applications in Medicinal Plant Monitoring and Quality Assessment: A Review

inferred← citeshttps://doi.org/10.3390/su16135748openalex-snapshot

Precision Farming Multimodal Technologies Using Optical Sensors for the Detection of Citrus Tristeza Virus Endemics

inferred← citeshttps://doi.org/10.3390/su17198908openalex-snapshot

UAV-Based Multispectral Imagery for Area-Wide Sustainable Tree Risk Management

inferred← citeshttps://doi.org/10.3390/su18189410openalex-snapshot

Seeing the Green from Above: A Review of Remote Sensing Techniques for Vegetation Cover Discrimination

inferred← citeshttps://doi.org/10.34133/plantphenomics.0188openalex-snapshot

Detection and Identification of Tassel States at Different Maize Tasseling Stages Using UAV Imagery and Deep Learning

inferred← citeshttps://doi.org/10.37391/ijeer.12bdf02openalex-snapshot

Development of Smart Agriculture to detect the Arabica Coffee Leaf Disease using IAFSA based MSAB with Channel and Spatial Attention Network

inferred← citeshttps://doi.org/10.3788/lop251606openalex-snapshot

基于光谱解混与空间建模的蟹塘水草机载高光谱成像检测方法

inferred← citeshttps://doi.org/10.4018/979-8-3373-8037-7.ch005openalex-snapshot

GeoAI-Driven Sustainable Precision Agriculture

inferred← citeshttps://doi.org/10.4018/979-8-3693-0578-2.ch009openalex-snapshot

Machine Learning in UAV-Assisted Smart Farming

inferred← citeshttps://doi.org/10.4018/979-8-3693-0774-8.ch003openalex-snapshot

Ethical Considerations in Drone Cybersecurity

inferred← citeshttps://doi.org/10.4081/jae.2025.1749openalex-snapshot

Monitoring water-stressed spring tea canopy temperature using UAV-derived indices and clustering models

inferred← citeshttps://doi.org/10.48044/jauf.2025.015openalex-snapshot

Unmanned Aerial Vehicle (UAV) in Tree Risk Assessment (TRA): A Systematic Review

inferred← citeshttps://doi.org/10.52783/jes.1375openalex-snapshot

Revolutionizing Agriculture IoT and Random Forest Algorithm for Crop Monitoring and Disease Prediction

inferred← citeshttps://doi.org/10.5772/intechopen.1010104openalex-snapshot

Agricultural UAVs in Recent Advances, Innovations and Applications

inferred← citeshttps://doi.org/10.58830/ozgur.pub1230.c4964openalex-snapshot

Tarımsal İzlemede İHA Tabanlı RGB Görüntülerin Değerlendirilmesi: Farklı Filtreleme Stratejilerinin Nesne Ayrıştırma Başarımı Üzerine Karşılaştırmalı Bir Analiz

inferred← citeshttps://doi.org/10.9787/kjbs.2024.56.4.439openalex-snapshot

The Trap of Presumption: A Case Study of Agricultural Research for Early Detection of Brown Planthopper Damage in Rice Fields

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