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An Automatic Random Forest-OBIA Algorithm for Early Weed Mapping between and within Crop Rows Using UAV Imagery

https://doi.org/10.3390/rs10020285
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What this work says

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

inferredcites →https://doi.org/10.1007/s11119-008-9097-6openalex-snapshot
Beyond patch spraying: site-specific weed management with several herbicides
inferredcites →https://doi.org/10.1007/s11119-013-9304-yopenalex-snapshot
Broad-scale cruciferous weed patch classification in winter wheat using QuickBird imagery for in-season site-specific control
inferredcites →https://doi.org/10.1007/s11119-015-9415-8openalex-snapshot
Early season weed mapping in sunflower using UAV technology: variability of herbicide treatment maps against weed thresholds
inferredcites →https://doi.org/10.1007/s11119-016-9468-3openalex-snapshot
Assessing the potential of images from unmanned aerial vehicles (UAV) to support herbicide patch spraying in maize
inferredcites →https://doi.org/10.1007/s11119-016-9476-3openalex-snapshot
Fleets of robots for environmentally-safe pest control in agriculture
inferredcites →https://doi.org/10.1007/s12518-013-0120-xopenalex-snapshot
UAV for 3D mapping applications: a review
inferredcites →https://doi.org/10.1007/s13593-016-0405-7openalex-snapshot
Object-based early monitoring of a grass weed in a grass crop using high resolution UAV imagery
inferredcites →https://doi.org/10.1016/j.asoc.2015.08.027openalex-snapshot
A semi-supervised system for weed mapping in sunflower crops using unmanned aerial vehicles and a crop row detection method
inferredcites →https://doi.org/10.1016/j.biosystemseng.2017.11.003openalex-snapshot
On-line crop/weed discrimination through the Mahalanobis distance from images in maize fields
inferredcites →https://doi.org/10.1016/j.compag.2007.05.008openalex-snapshot
Autonomous robotic weed control systems: A review
inferredcites →https://doi.org/10.1016/j.compag.2015.03.019openalex-snapshot
An automatic object-based method for optimal thresholding in UAV images: Application for vegetation detection in herbaceous crops
inferredcites →https://doi.org/10.1016/j.cropro.2012.03.010openalex-snapshot
Ecology and management of weeds under conservation agriculture: A review
inferredcites →https://doi.org/10.1016/j.eswa.2015.10.043openalex-snapshot
Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery
inferredcites →https://doi.org/10.1016/j.isprsjprs.2011.11.002openalex-snapshot
An assessment of the effectiveness of a random forest classifier for land-cover classification
inferredcites →https://doi.org/10.1016/j.isprsjprs.2013.09.014openalex-snapshot
Geographic Object-Based Image Analysis – Towards a new paradigm
inferredcites →https://doi.org/10.1016/j.isprsjprs.2013.11.018openalex-snapshot
Automated parameterisation for multi-scale image segmentation on multiple layers
inferredcites →https://doi.org/10.1016/j.isprsjprs.2014.12.026openalex-snapshot
Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery
inferredcites →https://doi.org/10.1016/j.isprsjprs.2015.03.002openalex-snapshot
Random Forest and Rotation Forest for fully polarized SAR image classification using polarimetric and spatial features
inferredcites →https://doi.org/10.1016/j.isprsjprs.2015.03.016openalex-snapshot
Identification of damage in buildings based on gaps in 3D point clouds from very high resolution oblique airborne images
inferredcites →https://doi.org/10.1016/j.isprsjprs.2016.01.011openalex-snapshot
Random forest in remote sensing: A review of applications and future directions
inferredcites →https://doi.org/10.1016/j.jag.2012.01.002openalex-snapshot
An evaluation of ensemble classifiers for mapping Natura 2000 heathland in Belgium using spaceborne angular hyperspectral (CHRIS/Proba) imagery
inferredcites →https://doi.org/10.1016/j.jag.2013.11.009openalex-snapshot
Area-based and location-based validation of classified image objects
inferredcites →https://doi.org/10.1016/j.jag.2016.01.011openalex-snapshot
A systematic comparison of different object-based classification techniques using high spatial resolution imagery in agricultural environments
inferredcites →https://doi.org/10.1016/j.rse.2013.04.005openalex-snapshot
High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision
inferredcites →https://doi.org/10.1016/j.rse.2015.09.011openalex-snapshot
Optimum spectral and geometric parameters for early detection of laurel wilt disease in avocado
inferredcites →https://doi.org/10.1017/s0043174500057386openalex-snapshot
Use of Ecophysiological Models for Crop-Weed Interference: The Critical Period of Weed Interference
inferredcites →https://doi.org/10.1017/s0043174500081753openalex-snapshot
The Concept and Application of Early Economic Period Threshold: The Case of DCPA in Onions (Allium Cepa)
inferredcites →https://doi.org/10.1017/s0043174500082722openalex-snapshot
Influence of the Relative Time of Emergence of Wild Oat (Avena fatua) on Yield Loss of Barley (Hordeum vulgare) and Wheat (Triticum aestivum)
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1080/01431160412331269698openalex-snapshot
Random forest classifier for remote sensing classification
inferredcites →https://doi.org/10.1109/icra.2017.7989347openalex-snapshot
UAV-based crop and weed classification for smart farming
inferredcites →https://doi.org/10.1109/tsmc.1979.4310076openalex-snapshot
A Threshold Selection Method from Gray-Level Histograms
inferredcites →https://doi.org/10.1111/j.1365-3180.2006.00504.xopenalex-snapshot
Practical experiences with a system for site‐specific weed control in arable crops using real‐time image analysis and GPS‐controlled patch spraying
inferredcites →https://doi.org/10.1111/j.1365-3180.2007.00553.xopenalex-snapshot
Mapping Ridolfia segetum patches in sunflower crop using remote sensing
inferredcites →https://doi.org/10.1111/j.1365-3180.2010.00829.xopenalex-snapshot
Weed detection for site‐specific weed management: mapping and real‐time approaches
inferredcites →https://doi.org/10.1111/j.1365-3180.2011.00876.xopenalex-snapshot
Weed discrimination using ultrasonic sensors
inferredcites →https://doi.org/10.1117/1.jrs.10.036018openalex-snapshot
Cotton growth modeling and assessment using unmanned aircraft system visual-band imagery
inferredcites →https://doi.org/10.1117/1.jrs.11.036013openalex-snapshot
Spatio-temporal evaluation of plant height in corn via unmanned aerial systems
inferredcites →https://doi.org/10.1371/journal.pone.0077151openalex-snapshot
Weed Mapping in Early-Season Maize Fields Using Object-Based Analysis of Unmanned Aerial Vehicle (UAV) Images
inferredcites →https://doi.org/10.1371/journal.pone.0130479openalex-snapshot
High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology
inferredcites →https://doi.org/10.14358/pers.70.5.627openalex-snapshot
Thematic Map Comparison
inferredcites →https://doi.org/10.14358/pers.72.7.799openalex-snapshot
Object-based Detailed Vegetation Classification with Airborne High Spatial Resolution Remote Sensing Imagery
inferredcites →https://doi.org/10.1614/0043-1745(2002)050[0773:cpfwct]2.0.co;2openalex-snapshot
Critical period for weed control: the concept and data analysis
inferredcites →https://doi.org/10.1614/ws-07-126.1openalex-snapshot
Integrated Weed Management: Knowledge-Based Weed Management Systems
inferredcites →https://doi.org/10.1614/ws-d-11-00183.1openalex-snapshot
Why Early Season Weed Control Is Important in Maize
inferredcites →https://doi.org/10.1614/ws-d-13-00050.1openalex-snapshot
An Imagery-Based Weed Cover Threshold Established Using Expert Knowledge
inferredcites →https://doi.org/10.1614/wt-03-170r1openalex-snapshot
Detection of Weed Species in Soybean Using Multispectral Digital Images
inferredcites →https://doi.org/10.1614/wt-04-272r.1openalex-snapshot
Response of Japanese Stiltgrass (Microstegium vimineum) to Application Timing, Rate, and Frequency of Postemergence Herbicides1
inferredcites →https://doi.org/10.17221/599/2012-pseopenalex-snapshot
Impact of site-specific weed management on herbicide savings and winter wheat yield
inferredcites →https://doi.org/10.2747/1548-1603.49.5.623openalex-snapshot
An Evaluation of Bagging, Boosting, and Random Forests for Land-Cover Classification in Cape Cod, Massachusetts, USA
inferredcites →https://doi.org/10.32614/rj-2009-016openalex-snapshot
Rattle: A Data Mining GUI for R
inferredcites →https://doi.org/10.3389/fpls.2017.00421openalex-snapshot
High-Throughput Phenotyping of Sorghum Plant Height Using an Unmanned Aerial Vehicle and Its Application to Genomic Prediction Modeling
inferredcites →https://doi.org/10.3390/rs61110335openalex-snapshot
Combined Spectral and Spatial Modeling of Corn Yield Based on Aerial Images and Crop Surface Models Acquired with an Unmanned Aircraft System
inferredcites →https://doi.org/10.3390/rs61110395openalex-snapshot
Estimating Biomass of Barley Using Crop Surface Models (CSMs) Derived from UAV-Based RGB Imaging
inferredcites →https://doi.org/10.3390/rs70809655openalex-snapshot
An Evaluation of Different Training Sample Allocation Schemes for Discrete and Continuous Land Cover Classification Using Decision Tree-Based Algorithms
inferredcites →https://doi.org/10.3390/rs9070647openalex-snapshot
Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight
inferredcites →https://doi.org/10.3390/s150305609openalex-snapshot
Quantifying Efficacy and Limits of Unmanned Aerial Vehicle (UAV) Technology for Weed Seedling Detection as Affected by Sensor Resolution
inferredcites →https://doi.org/10.5073/bbch0515openalex-snapshot
Growth stages of mono-and dicotyledonous plants

What points at this work

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

inferred← citeshttps://doi.org/10.2139/ssrn.4188682openalex-extracted
A Region-Based Convolution Neural Network for Crop and Weed Classification in Smart Agriculture
inferred← citeshttps://doi.org/10.2139/ssrn.4524871openalex-extracted
Improved U-Net-Based Winter Wheat Crop Row Detection Method Using Texture Enhancement
inferred← citeshttps://doi.org/10.2139/ssrn.4535834openalex-extracted
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inferred← citeshttps://doi.org/10.1002/2050-7038.12836openalex-snapshot
An intelligent grid synchronization technique for microgrid system with smooth power quality using chaotic grey wolf optimization‐random forest algorithm scheme
inferred← citeshttps://doi.org/10.1002/9781119785873.ch10openalex-snapshot
Smart Environment Monitoring Models Using Cloud‐Based Data Analytics: A Comprehensive Study
inferred← citeshttps://doi.org/10.1002/aqc.3357openalex-snapshot
Application of multiplatform, multispectral remote sensors for mapping intertidal macroalgae: A comparative approach
inferred← citeshttps://doi.org/10.1002/ppj2.70034openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/ps.7233openalex-snapshot
Detection of Ecballium elaterium in hedgerow olive orchards using a low‐cost uncrewed aerial vehicle and open‐source algorithms
inferred← citeshttps://doi.org/10.1002/ps.7443openalex-snapshot
Improved weed mapping in corn fields by combining UAV ‐based spectral, textural, structural, and thermal measurements
inferred← citeshttps://doi.org/10.1007/978-3-030-38712-9_1openalex-snapshot
A Comprehensive Review on the Use of AI in UAV Communications: Enabling Technologies, Applications, and Challenges
inferred← citeshttps://doi.org/10.1007/978-3-030-44402-0_7openalex-snapshot
Site-Specific Based Models
inferred← citeshttps://doi.org/10.1007/978-3-030-64258-7_13openalex-snapshot
Metrics in Precision Agriculture Using Multispectral Images: Review and Evaluation
inferred← citeshttps://doi.org/10.1007/978-3-030-84148-5_3openalex-snapshot
Machine Learning Technology and Its Current Implementation in Agriculture
inferred← citeshttps://doi.org/10.1007/978-3-030-90083-0_11openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-04524-0_18openalex-snapshot
Deep Learning Approach for IOT-Based Multiclass Weed Classification Using YOLOv5
inferred← citeshttps://doi.org/10.1007/978-3-031-10545-6_22openalex-snapshot
LULC Classification Performance of Supervised and Unsupervised Algorithms on UAV-Orthomosaics
inferred← citeshttps://doi.org/10.1007/978-3-031-36616-1_39openalex-snapshot
Object Detection for Rescue Operations by High-Altitude Infrared Thermal Imaging Collected by Unmanned Aerial Vehicles
inferred← citeshttps://doi.org/10.1007/978-3-031-38669-5_5openalex-snapshot
IoT-Based Unmanned Aerial Vehicle (UAV) for Smart Farming
inferred← citeshttps://doi.org/10.1007/978-3-031-91014-2_4openalex-snapshot
The Role of Unmanned Aerial Vehicles and Sensor Technology in Site-Specific Weed Management
inferred← citeshttps://doi.org/10.1007/978-3-031-96534-0_5openalex-snapshot
Weed Management—Identification and Treatment
inferred← citeshttps://doi.org/10.1007/978-3-032-01536-5_47openalex-snapshot
Agriculture and AI: Transforming Farming Practices Through Innovation and Automation
inferred← citeshttps://doi.org/10.1007/978-3-032-26217-2_15openalex-snapshot
Band-Aware Transformer (BAT-Former) for General Image Understanding
inferred← citeshttps://doi.org/10.1007/978-981-16-9991-7_3openalex-snapshot
A Deep Learning-Based Detection System of Multi-class Crops and Orchards Using a UAV
inferred← citeshttps://doi.org/10.1007/978-981-19-2027-1_3openalex-snapshot
Unmanned Aerial Vehicle (UAV) Applications in Cotton Production
inferred← citeshttps://doi.org/10.1007/978-981-99-3754-7_12openalex-snapshot
An Intelligent Vision-Guided Framework of the Unmanned Aerial System for Precision Agriculture
inferred← citeshttps://doi.org/10.1007/978-981-99-8684-2_12openalex-snapshot
Drone-Based Intelligent Spraying of Pesticides: Current Challenges and Its Future Prospects
inferred← citeshttps://doi.org/10.1007/s00271-023-00907-1openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s00521-023-09320-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10661-023-11004-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11042-021-11203-5openalex-snapshot
Residual-capsule networks with threshold convolution for segmentation of wheat plantation rows in UAV images
inferred← citeshttps://doi.org/10.1007/s11042-023-16105-2openalex-snapshot
Machine learning in agriculture: a review of crop management applications
inferred← citeshttps://doi.org/10.1007/s11069-023-06186-5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11119-019-09635-zopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11119-021-09786-yopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11119-021-09808-9openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11119-022-09904-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11119-022-09982-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11119-024-10124-1openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11119-024-10155-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11119-026-10348-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11707-024-1109-yopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11831-022-09761-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11852-022-00886-zopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s12145-020-00531-zopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s41348-025-01082-5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s41348-025-01209-8openalex-snapshot
Automatic weed detection in paddy field: a review
inferred← citeshttps://doi.org/10.1007/s43154-022-00086-5openalex-snapshot
Review of Current Robotic Approaches for Precision Weed Management
inferred← citeshttps://doi.org/10.1016/b978-0-12-814391-9.00004-2openalex-snapshot
Tutorial I: Weed detection
inferred← citeshttps://doi.org/10.1016/b978-0-443-24001-0.00013-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/bs.agron.2019.08.004openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.aiia.2021.11.004openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.aiia.2023.09.002openalex-snapshot
Machine learning for weed–plant discrimination in agriculture 5.0: An in-depth review
inferred← citeshttps://doi.org/10.1016/j.aiia.2024.06.005openalex-snapshot
A comprehensive survey on weed and crop classification using machine learning and deep learning
inferred← citeshttps://doi.org/10.1016/j.atech.2022.100153openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.atech.2023.100231openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.atech.2023.100249openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.atech.2023.100323openalex-snapshot
Precision farming technologies for crop protection: A meta-analysis
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.biosystemseng.2018.10.018openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.compag.2018.10.016openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.compag.2020.105385openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.compag.2020.105500openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.compag.2020.105903openalex-snapshot
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inferred← citeshttps://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
inferred← citeshttps://doi.org/10.1016/j.compag.2022.107017openalex-snapshot
Drones in agriculture: A review and bibliometric analysis
inferred← citeshttps://doi.org/10.1016/j.compag.2022.107119openalex-snapshot
Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming
inferred← citeshttps://doi.org/10.1016/j.compag.2022.107558openalex-snapshot
On-farm evaluation of UAV-based aerial imagery for season-long weed monitoring under contrasting management and pedoclimatic conditions in wheat
inferred← citeshttps://doi.org/10.1016/j.compag.2023.107755openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.compag.2024.108859openalex-snapshot
Spectral mixture analysis for weed traits identification under varying resolutions and growth stages
inferred← citeshttps://doi.org/10.1016/j.compag.2024.108867openalex-snapshot
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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.2026.111736openalex-snapshot
Design and development of a low-cost industrial prototype of spot-specific spraying system for potato weed detection using deep learning
inferred← citeshttps://doi.org/10.1016/j.cropro.2019.105010openalex-snapshot
Weed surveys and weed mapping in Europe: State of the art and future tasks
inferred← citeshttps://doi.org/10.1016/j.cropro.2025.107206openalex-snapshot
Intelligent weed management using aerial image processing and precision herbicide spraying: An overview
inferred← citeshttps://doi.org/10.1016/j.ecoinf.2023.102305openalex-snapshot
Adoption of Unmanned Aerial Vehicle (UAV) imagery in agricultural management: A systematic literature review
inferred← citeshttps://doi.org/10.1016/j.eja.2020.126201openalex-snapshot
A UAV-based framework for crop lodging assessment
inferred← citeshttps://doi.org/10.1016/j.future.2019.04.051openalex-snapshot
Agent-based simulation of unmanned aerial vehicles in civilian applications: A systematic literature review and research directions
inferred← citeshttps://doi.org/10.1016/j.geomorph.2024.109070openalex-snapshot
Mapping stony rise landforms using a novel remote sensing, geophysical, and machine learning approach
inferred← citeshttps://doi.org/10.1016/j.ifacol.2019.12.530openalex-snapshot
Distributed Coverage Control of Quadrotor Multi-UAV Systems for Precision Agriculture
inferred← citeshttps://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
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2020.07.017openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jag.2019.102008openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jhydrol.2023.130229openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.rineng.2024.101870openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.rsase.2023.100941openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.rsase.2025.101553openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.rse.2022.113374openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.scitotenv.2021.148539openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.srs.2025.100352openalex-snapshot
Weed classification in sugarcane fields in Northeast Thailand from multi-temporal Sentinel-1 and Sentinel-2 data together with random forest algorithm
inferred← citeshttps://doi.org/10.1016/j.suscom.2020.100506openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.tplants.2018.11.007openalex-snapshot
Perspectives for Remote Sensing with Unmanned Aerial Vehicles in Precision Agriculture
inferred← citeshttps://doi.org/10.1021/acs.est.3c01269openalex-snapshot
Glyphosate Separating and Sensing for Precision Agriculture and Environmental Protection in the Era of Smart Materials
inferred← citeshttps://doi.org/10.1038/s41598-023-33042-0openalex-snapshot
Towards reducing chemical usage for weed control in agriculture using UAS imagery analysis and computer vision techniques
inferred← citeshttps://doi.org/10.1038/s41598-024-82055-wopenalex-snapshot
Legume content estimation from UAV image in grass-legume meadows: comparison methods based on the UAV coverage vs. field biomass
inferred← citeshttps://doi.org/10.1038/s41598-026-37475-1openalex-snapshot
Automated weed segmentation with knowledge based labeling for machine learning applications
inferred← citeshttps://doi.org/10.1061/9780784483893.109openalex-snapshot
Analysis of Flight Parameters on UAV Semantic Segmentation Performance for Highway Infrastructure Monitoring
inferred← citeshttps://doi.org/10.1061/9780784483893.110openalex-snapshot
AI-Driven 3D Point Cloud-Based Highway Infrastructure Monitoring System Using UAV
inferred← citeshttps://doi.org/10.1063/5.0342942openalex-snapshot
Modern and evolutionary methods of agricultural field health monitoring: UAV imagery
inferred← citeshttps://doi.org/10.1080/0035919x.2024.2409629openalex-snapshot
Application of unmanned aerial systems for crop discrimination in smallholder farming systems: a systematic review of trends, technical challenges and opportunities
inferred← citeshttps://doi.org/10.1080/01431161.2019.1706112openalex-snapshot
Deep learning versus Object-based Image Analysis (OBIA) in weed mapping of UAV imagery
inferred← citeshttps://doi.org/10.1080/09064710.2021.2024874openalex-snapshot
RETRACTED ARTICLE: Computer development based embedded systems in precision agriculture: tools and application
inferred← citeshttps://doi.org/10.1080/10496505.2019.1638264openalex-snapshot
Data-Driven Decision Making in Precision Agriculture: The Rise of Big Data in Agricultural Systems
inferred← citeshttps://doi.org/10.1080/1343943x.2020.1829490openalex-snapshot
Discriminating crops/weeds in an upland rice field from UAV images with the SLIC-RF algorithm
inferred← citeshttps://doi.org/10.1080/1343943x.2023.2178469openalex-snapshot
Monitoring spatial and time-series variations in red crown rot damage of soybean in farmer fields based on UAV remote sensing
inferred← citeshttps://doi.org/10.1080/13682199.2019.1624442openalex-snapshot
On the application of remote sensing towards the estimation of cultivated land lost to urbanization
inferred← citeshttps://doi.org/10.1080/19475705.2022.2098066openalex-snapshot
Mapping burned areas and land-uses in Kangaroo Island using an object-based image classification framework and Landsat 8 Imagery from Google Earth Engine
inferred← citeshttps://doi.org/10.1080/22797254.2021.1951623openalex-snapshot
Comparison and assessment of different object-based classifications using machine learning algorithms and UAVs multispectral imagery: a case study in a citrus orchard and an onion crop
inferred← citeshttps://doi.org/10.1088/1755-1315/1102/1/012019openalex-snapshot
High-Resolution Mapping Using Digital Imagery of Unmanned Aerial Vehicle (UAV) at Quarry Area, Machang, Kelantan
inferred← citeshttps://doi.org/10.1109/3cbit57391.2022.00020openalex-snapshot
Research Fronts on Plant Protection Unmanned Aerial Vehicle (UAV) from the Joint of Papers and Patents
inferred← citeshttps://doi.org/10.1109/access.2023.3315606openalex-snapshot
Digital Agriculture: Mapping Knowledge Structure and Trends
inferred← citeshttps://doi.org/10.1109/access.2024.3390581openalex-snapshot
Evaluation of Machine Learning Approaches for Precision Farming in Smart Agriculture System: A Comprehensive Review
inferred← citeshttps://doi.org/10.1109/agro-geoinformatics.2019.8820632openalex-snapshot
Object-based random forest classification for detecting plastic-mulched landcover from Gaofen-2 and Landsat-8 OLI fused data
inferred← citeshttps://doi.org/10.1109/agro-geoinformatics262780.2024.10660674openalex-snapshot
Winter wheat classification within heterogeneous agricultural landscapes
inferred← citeshttps://doi.org/10.1109/ccem60455.2023.00042openalex-snapshot
Verdant Visions: Exploring the Frontier of Peppermint Disease Detection Through CNN and Random Forest
inferred← citeshttps://doi.org/10.1109/cisct62494.2024.11134262openalex-snapshot
Deep Learning in Brain Tumor Recognition: “A Critical Review of Techniques, Limitations, and Future Prospects”
inferred← citeshttps://doi.org/10.1109/dcoss.2019.00080openalex-snapshot
Data Acquisition and Analysis Methods in UAV- based Applications for Precision Agriculture
inferred← citeshttps://doi.org/10.1109/iccmc48092.2020.iccmc-000178openalex-snapshot
Weed Identification using Convolutional Neural Network and Convolutional Neural Network Architectures
inferred← citeshttps://doi.org/10.1109/iccsre.2019.8807604openalex-snapshot
Evaluation of Agricultural Precision Algorithms on UAV Images
inferred← citeshttps://doi.org/10.1109/ictmim65579.2025.10987979openalex-snapshot
Optimizing Crop Spraying with Smart Drones using Deep Neural Networks and Image Processing
inferred← citeshttps://doi.org/10.1109/ipta.2019.8936091openalex-snapshot
Deep features and One-class classification with unsupervised data for weed detection in UAV images
inferred← citeshttps://doi.org/10.1109/iscaie64985.2025.11080940openalex-snapshot
Autonomous Drone-Based Border Surveillance Using Real-Time Object Detection with Yolo
inferred← citeshttps://doi.org/10.1109/jstars.2021.3094973openalex-snapshot
Crop Mapping Using Sentinel Full-Year Dual-Polarized SAR Data and a CPU-Optimized Convolutional Neural Network With Two Sampling Strategies
inferred← citeshttps://doi.org/10.1109/jstars.2021.3136228openalex-snapshot
Analysis on Effective UAS Survey Conditions for Classification of Coastal Sediments
inferred← citeshttps://doi.org/10.1109/jstars.2025.3570750openalex-snapshot
An Integrated Sample-Free Method for Agricultural Field Delineation From High-Resolution Remote Sensing Imagery
inferred← citeshttps://doi.org/10.1109/lra.2019.2926957openalex-snapshot
Fast Classification of Large Germinated Fields Via High-Resolution UAV Imagery
inferred← citeshttps://doi.org/10.1109/tafe.2026.3690817openalex-snapshot
Edge Deployable Weed Detection in UAV Imagery Using YOLOv12 With Scale and Motion Aware Data Augmentation
inferred← citeshttps://doi.org/10.1109/tgrs.2024.3425673openalex-snapshot
A Deep Learning Method for Cultivated Land Parcels’ (CLPs) Delineation From High-Resolution Remote Sensing Images With High-Generalization Capability
inferred← citeshttps://doi.org/10.1109/urucon63440.2024.10850067openalex-snapshot
Real-Time Detection of UAV Small Target’s Infrared Imaging via OSTD-YOLOv8
inferred← citeshttps://doi.org/10.1111/grs.12277openalex-snapshot
Counting of Pennisetum alopecuroides at heading stage in a grazed pasture using images from an unmanned aerial vehicle
inferred← citeshttps://doi.org/10.1111/grs.12288openalex-snapshot
Discriminating Pennisetum alopecuoides plants in a grazed pasture from unmanned aerial vehicles using object‐based image analysis and random forest classifier
inferred← citeshttps://doi.org/10.1117/1.jrs.15.014516openalex-snapshot
Use of high-resolution unmanned aerial systems imagery and machine learning to evaluate grain sorghum tolerance to mesotrione
inferred← citeshttps://doi.org/10.1117/12.2304739openalex-snapshot
Experimental approach to detect water stress in ornamental plants using sUAS-imagery
inferred← citeshttps://doi.org/10.1117/12.2564696openalex-snapshot
The future of cooperative air and ground phenotyping
inferred← citeshttps://doi.org/10.1142/s2301385022500029openalex-snapshot
A Novel Framework for Multiple Ground Target Detection, Recognition and Inspection in Precision Agriculture Applications Using a UAV
inferred← citeshttps://doi.org/10.1145/3447993.3483273openalex-snapshot
Visage
inferred← citeshttps://doi.org/10.1155/2021/4310321openalex-snapshot
Recognition of Ziziphus lotus through Aerial Imaging and Deep Transfer Learning Approach
inferred← citeshttps://doi.org/10.1155/2022/5385505openalex-snapshot
Application and Potential of Drone Technology in Oil Palm Plantation: Potential and Limitations
inferred← citeshttps://doi.org/10.11591/ijece.v12i6.pp6756-6767openalex-snapshot
Hybrid features and ensembles of convolution neural networks for weed detection
inferred← citeshttps://doi.org/10.1186/s13007-019-0547-0openalex-snapshot
An efficient RGB-UAV-based platform for field almond tree phenotyping: 3-D architecture and flowering traits
inferred← citeshttps://doi.org/10.1186/s40538-021-00217-8openalex-snapshot
Drone and sensor technology for sustainable weed management: a review
inferred← citeshttps://doi.org/10.1270/jsbbs.21069openalex-snapshot
High-throughput field crop phenotyping: current status and challenges
inferred← citeshttps://doi.org/10.13031/trans.13067openalex-snapshot
Cotton Yield Estimation from UAV-Based Plant Height
inferred← citeshttps://doi.org/10.13140/rg.2.2.35568.38404openalex-snapshot
Using Advanced Proximal Sensing and Genotyping Tools Combined with Bigdata Analysis Methods to Improve Soybean Yield
inferred← citeshttps://doi.org/10.1371/journal.pone.0218132openalex-snapshot
Automatic UAV-based detection of Cynodon dactylon for site-specific vineyard management
inferred← citeshttps://doi.org/10.1371/journal.pone.0250665openalex-snapshot
Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits
inferred← citeshttps://doi.org/10.1515/biol-2022-0713openalex-snapshot
Artificial intelligence and internet of things oriented sustainable precision farming: Towards modern agriculture
inferred← citeshttps://doi.org/10.15302/j-fase-2024564openalex-snapshot
Advancing agriculture with machine learning: a new frontier in weed management
inferred← citeshttps://doi.org/10.1590/0103-8478cr20210002openalex-snapshot
A lettuce moisture detection method based on terahertz time-domain spectroscopy
inferred← citeshttps://doi.org/10.18066/inic0115.23openalex-snapshot
CLASSIFICAÇÃO E SEGMENTAÇÃO DE PLANTAS DANINHAS EM PASTAGEM CULTIVADA UTILIZANDO O ALGORITMO K-NEAREST NEIGHBORS
inferred← citeshttps://doi.org/10.18494/sam4364openalex-snapshot
Locating Open-field Broccoli Plants with Unmanned Aerial Vehicle Photogrammetry and Object Detection Algorithm: A Practical Prediction Approach
inferred← citeshttps://doi.org/10.19184/j-agt.v16i02.28567openalex-snapshot
Aplikasi Citra Drone untuk Klasifikasi Vegetasi di Cagar Alam Curah Manis Sempolan 1 Menggunakan Metode Manual, Object Base Image Analysis (OBIA), dan K-Means
inferred← citeshttps://doi.org/10.20944/preprints201809.0088.v1openalex-snapshot
Deep Learning with Unsupervised Data Labeling for Weeds Detection on UAV Images
inferred← citeshttps://doi.org/10.20944/preprints202312.0441.v1openalex-snapshot
Harnessing Drones, Doves and Sentinel-2 Imagery for Assessing the Composition and Trajectory of Restoration
inferred← citeshttps://doi.org/10.21162/pakjas/19.8036openalex-snapshot
WEED DETECTION IN WHEAT CROP USING UAV for PRECISION AGRICULTURE
inferred← citeshttps://doi.org/10.2139/ssrn.5378473openalex-snapshot
Effect of Mowing, Imaging Technique, and Annotation Method on Weed Detection in Turfgrass Using Yolo
inferred← citeshttps://doi.org/10.22214/ijraset.2023.50451openalex-snapshot
Weed Detection in Agricultural Fields
inferred← citeshttps://doi.org/10.24011/barofd.1639471openalex-snapshot
Multispektral İHA Görüntüleri Kullanılarak Nesne Tabanlı Görüntü Analizi ile Ağaç Tespiti ve NDVI Tabanlı Bitki Sağlığı Analizi
inferred← citeshttps://doi.org/10.25165/j.ijabe.20211401.5714openalex-snapshot
Review of agricultural spraying technologies for plant protection using unmanned aerial vehicle (UAV)
inferred← citeshttps://doi.org/10.33440/j.ijpaa.20190201.0018openalex-snapshot
Exploring the potential of UAV imagery for variable rate spraying in cotton defoliation application
inferred← citeshttps://doi.org/10.33440/j.ijpaa.20220501.190openalex-snapshot
Semi-supervised learning for accurate weed mapping of UAV imagery
inferred← citeshttps://doi.org/10.3389/fagro.2026.1706873openalex-snapshot
Enhancing weed detection in wheat with hybrid attention mechanism CBAM: a comparative study with deep learning approaches
inferred← citeshttps://doi.org/10.3389/fpls.2019.01472openalex-snapshot
High-Throughput System for the Early Quantification of Major Architectural Traits in Olive Breeding Trials Using UAV Images and OBIA Techniques
inferred← citeshttps://doi.org/10.3389/fpls.2021.702626openalex-snapshot
Unmanned Aerial System-Based Weed Mapping in Sod Production Using a Convolutional Neural Network
inferred← citeshttps://doi.org/10.3389/fpls.2022.927368openalex-snapshot
Semi-supervised Learning for Weed and Crop Segmentation Using UAV Imagery
inferred← citeshttps://doi.org/10.3389/fpls.2023.1143326openalex-snapshot
Boosting precision crop protection towards agriculture 5.0 via machine learning and emerging technologies: A contextual review
inferred← citeshttps://doi.org/10.3389/fpls.2024.1298791openalex-snapshot
GranoScan: an AI-powered mobile app for in-field identification of biotic threats of wheat
inferred← citeshttps://doi.org/10.3389/fpls.2024.1414181openalex-snapshot
Quantification of species composition in grass-clover swards using RGB and multispectral UAV imagery and machine learning
inferred← citeshttps://doi.org/10.3389/fsufs.2022.1053921openalex-snapshot
Artificial intelligence-based decision support systems in smart agriculture: Bibliometric analysis for operational insights and future directions
inferred← citeshttps://doi.org/10.3390/aerospace10070612openalex-snapshot
Task Parameter Planning Algorithm for UAV Area Complete Coverage in EO Sector Scanning Mode
inferred← citeshttps://doi.org/10.3390/agriculture10070256openalex-snapshot
Prospects of Improving Agricultural and Water Productivity through Unmanned Aerial Vehicles
inferred← citeshttps://doi.org/10.3390/agriculture11050387openalex-snapshot
Early Weed Detection Using Image Processing and Machine Learning Techniques in an Australian Chilli Farm
inferred← citeshttps://doi.org/10.3390/agriculture11101004openalex-snapshot
How Can Unmanned Aerial Vehicles Be Used for Detecting Weeds in Agricultural Fields?
inferred← citeshttps://doi.org/10.3390/agriculture12101541openalex-snapshot
Weed Detection in Peanut Fields Based on Machine Vision
inferred← citeshttps://doi.org/10.3390/agriculture14081378openalex-snapshot
Key Technologies of Intelligent Weeding for Vegetables: A Review
inferred← citeshttps://doi.org/10.3390/agriculture15040377openalex-snapshot
Machine Learning in Sustainable Agriculture: Systematic Review and Research Perspectives
inferred← citeshttps://doi.org/10.3390/agriculture8050065openalex-snapshot
Multi-Temporal Site-Specific Weed Control of Cirsium arvense (L.) Scop. and Rumex crispus L. in Maize and Sugar Beet Using Unmanned Aerial Vehicle Based Mapping
inferred← citeshttps://doi.org/10.3390/agriengineering2020012openalex-snapshot
UAV Detection of Sinapis arvensis Infestation in Alfalfa Plots Using Simple Vegetation Indices from Conventional Digital Cameras
inferred← citeshttps://doi.org/10.3390/agriengineering2020024openalex-snapshot
Mapping and Estimating Weeds in Cotton Using Unmanned Aerial Systems-Borne Imagery
inferred← citeshttps://doi.org/10.3390/agriengineering3020011openalex-snapshot
RFID and Drones: The Next Generation of Plant Inventory
inferred← citeshttps://doi.org/10.3390/agriengineering6030177openalex-snapshot
Advances in Sustainable Crop Management: Integrating Precision Agriculture and Proximal Sensing
inferred← citeshttps://doi.org/10.3390/agriengineering7110365openalex-snapshot
A Review of Crop Attribute Monitoring Technologies for General Agricultural Scenarios
inferred← citeshttps://doi.org/10.3390/agriengineering8050172openalex-snapshot
Mapping Sugarcane Weeds Using Spectral Signatures Derived from Spectroscopic Data and Multispectral Images
inferred← citeshttps://doi.org/10.3390/agriengineering8080337openalex-snapshot
Vision-Based Crop Row Detection for Autonomous Agricultural Navigation: A Systematic Review and Practical Perspective of Developing Cost-Effective Field Robots
inferred← citeshttps://doi.org/10.3390/agronomy10010140openalex-snapshot
A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops
inferred← citeshttps://doi.org/10.3390/agronomy10071027openalex-snapshot
Real-Time Detection of Strawberry Powdery Mildew Disease Using a Mobile Machine Vision System
inferred← citeshttps://doi.org/10.3390/agronomy11040749openalex-snapshot
Early Detection of Broad-Leaved and Grass Weeds in Wide Row Crops Using Artificial Neural Networks and UAV Imagery
inferred← citeshttps://doi.org/10.3390/agronomy11050880openalex-snapshot
Monitoring the Spatial Variability of Knapweed (Centaurea diluta Aiton) in Wheat Crops Using Geostatistics and UAV Imagery: Probability Maps for Risk Assessment in Site-Specific Control
inferred← citeshttps://doi.org/10.3390/agronomy11071435openalex-snapshot
Assessment of Weed Classification Using Hyperspectral Reflectance and Optimal Multispectral UAV Imagery
inferred← citeshttps://doi.org/10.3390/agronomy11091809openalex-snapshot
Using Remote Sensing and an Unmanned Aerial System for Weed Management in Agricultural Crops: A Review
inferred← citeshttps://doi.org/10.3390/agronomy13020528openalex-snapshot
Early-Season Mapping of Johnsongrass (Sorghum halepense), Common Cocklebur (Xanthium strumarium) and Velvetleaf (Abutilon theophrasti) in Corn Fields Using Airborne Hyperspectral Imagery
inferred← citeshttps://doi.org/10.3390/agronomy13030830openalex-snapshot
Weed Detection and Mapping of a Coffee Farm by a Remotely Piloted Aircraft System
inferred← citeshttps://doi.org/10.3390/agronomy13071780openalex-snapshot
Row Detection BASED Navigation and Guidance for Agricultural Robots and Autonomous Vehicles in Row-Crop Fields: Methods and Applications
inferred← citeshttps://doi.org/10.3390/agronomy14112697openalex-snapshot
Artificial Intelligence Applied to Support Agronomic Decisions for the Automatic Aerial Analysis Images Captured by UAV: A Systematic Review
inferred← citeshttps://doi.org/10.3390/agronomy15112600openalex-snapshot
Review and Assessment of Crop-Related Digital Tools for Agroecology
inferred← citeshttps://doi.org/10.3390/agronomy15122885openalex-snapshot
A Canopy Height Model Derived from Unmanned Aerial System Imagery Provides Late-Season Weed Detection and Explains Variation in Crop Yield
inferred← citeshttps://doi.org/10.3390/agronomy9110741openalex-snapshot
Three-Dimensional Morphological Measurement Method for a Fruit Tree Canopy Based on Kinect Sensor Self-Calibration
inferred← citeshttps://doi.org/10.3390/app10103456openalex-snapshot
Systematic Mapping Study on Remote Sensing in Agriculture
inferred← citeshttps://doi.org/10.3390/app112210701openalex-snapshot
Weed Detection in Rice Fields Using Remote Sensing Technique: A Review
inferred← citeshttps://doi.org/10.3390/app9040643openalex-snapshot
Impact of Texture Information on Crop Classification with Machine Learning and UAV Images
inferred← citeshttps://doi.org/10.3390/drones5020035openalex-snapshot
Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern Greece
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