On the public citation graph
Potential use of ground‐based sensor technologies for weed detection
0 signed · 230 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/9780470122563.ch3openalex-snapshot
Chlorophyll Fluorescence and Photosynthesis
inferredcites →https://doi.org/10.1006/jaer.1998.0334openalex-snapshot
Reduced Input of Herbicides by Use of Optoelectronic Sensors
inferredcites →https://doi.org/10.1006/jaer.1999.0519openalex-snapshot
Crop–weed Discrimination by Line Imaging Spectroscopy
inferredcites →https://doi.org/10.1007/978-90-481-9277-9_8openalex-snapshot
Detection and Identification of Weeds
inferredcites →https://doi.org/10.1007/s10343-008-0195-1openalex-snapshot
Precision farming for weed management: techniques
inferredcites →https://doi.org/10.1007/s11119-004-5321-1openalex-snapshot
A Review on Remote Sensing of Weeds in Agriculture
inferredcites →https://doi.org/10.1007/s11119-006-9015-8openalex-snapshot
Patchy weed distribution and site-specific weed control in winter cereals
inferredcites →https://doi.org/10.1007/s11119-008-9080-2openalex-snapshot
A comparison of crop data measured by two commercial sensors for variable-rate nitrogen application
inferredcites →https://doi.org/10.1007/s11119-009-9114-4openalex-snapshot
Laser rangefinder-based measuring of crop biomass under field conditions
inferredcites →https://doi.org/10.1007/s11119-009-9126-0openalex-snapshot
Discrimination of corn, grasses and dicot weeds by their UV-induced fluorescence spectral signature
inferredcites →https://doi.org/10.1007/s11119-010-9201-6openalex-snapshot
Automatic identification of crop and weed species with chlorophyll fluorescence induction curves
inferredcites →https://doi.org/10.1007/s11540-010-9173-yopenalex-snapshot
Weed Mapping—A Way to Reduce Herbicide Doses
inferredcites →https://doi.org/10.1016/j.biosystemseng.2004.11.010openalex-snapshot
Applications of Spectral Reflectance Techniques in Northern European Cereal Production: A Review
inferredcites →https://doi.org/10.1016/j.biosystemseng.2005.04.011openalex-snapshot
Weed Classification by Active Shape Models
inferredcites →https://doi.org/10.1016/j.biosystemseng.2006.11.009openalex-snapshot
Application Accuracy of a Machine Vision-controlled Robotic Micro-dosing System
inferredcites →https://doi.org/10.1016/j.biosystemseng.2008.05.003openalex-snapshot
Classification of crops and weeds extracted by active shape models
inferredcites →https://doi.org/10.1016/j.biosystemseng.2008.10.003openalex-snapshot
Estimation of the crop density of small grains using LiDAR sensors
inferredcites →https://doi.org/10.1016/j.biosystemseng.2011.09.011openalex-snapshot
Weed identification using an automated active shape matching (AASM) technique
inferredcites →https://doi.org/10.1016/j.compag.2004.03.006openalex-snapshot
Discrimination of sunflower, weed and soil by artificial neural networks
inferredcites →https://doi.org/10.1016/j.compag.2006.06.001openalex-snapshot
Development of machine vision and laser radar based autonomous vehicle guidance systems for citrus grove navigation
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.2007.06.002openalex-snapshot
Ground-based sensing system for weed mapping in cotton
inferredcites →https://doi.org/10.1016/j.compag.2007.12.007openalex-snapshot
Selection of the most efficient wavelength bands for discriminating weeds from crop
inferredcites →https://doi.org/10.1016/j.compag.2008.12.003openalex-snapshot
Weed image classification using Gabor wavelet and gradient field distribution
inferredcites →https://doi.org/10.1016/j.compag.2009.07.001openalex-snapshot
Improving in-row weed detection in multispectral stereoscopic images
inferredcites →https://doi.org/10.1016/j.compag.2010.08.005openalex-snapshot
Sensing technologies for precision specialty crop production
inferredcites →https://doi.org/10.1016/j.compag.2011.09.007openalex-snapshot
A review of methods and applications of the geometric characterization of tree crops in agricultural activities
inferredcites →https://doi.org/10.1016/j.compag.2011.10.018openalex-snapshot
Sequential support vector machine classification for small-grain weed species discrimination with special regard to Cirsium arvense and Galium aparine
inferredcites →https://doi.org/10.1016/j.compag.2012.04.001openalex-snapshot
A LIDAR-based crop height measurement system for Miscanthus giganteus
inferredcites →https://doi.org/10.1016/j.compag.2012.12.012openalex-snapshot
Potential of a terrestrial LiDAR-based system to characterise weed vegetation in maize crops
inferredcites →https://doi.org/10.1016/j.cropro.2005.08.018openalex-snapshot
Sensor-based weed detection and application of variable herbicide rates in real time
inferredcites →https://doi.org/10.1016/j.fcr.2011.02.003openalex-snapshot
Potential of field hyperspectral imaging as a non destructive method to assess leaf nitrogen content in Wheat
inferredcites →https://doi.org/10.1016/s0006-3495(99)76967-5openalex-snapshot
The Kautsky Curve Is a Built-in Barcode
inferredcites →https://doi.org/10.1016/s0168-1699(02)00223-5openalex-snapshot
Comparison of a Bayesian classifier with a multilayer feed-forward neural network using the example of plant/weed/soil discrimination
inferredcites →https://doi.org/10.1017/cbo9780511608629openalex-snapshot
Dynamics of Weed Populations
inferredcites →https://doi.org/10.1017/s0043174500092559openalex-snapshot
Characterizing spatial stability of weed populations using interpolated maps
inferredcites →https://doi.org/10.1017/s0890037x00042482openalex-snapshot
Economic Importance of Managing Spatially Heterogeneous Weed Populations
inferredcites →https://doi.org/10.1023/a:1009977903204openalex-snapshot
Robotic Weed Control System for Tomatoes
inferredcites →https://doi.org/10.1023/a:1015590520873openalex-snapshot
A Weed Species Spectral Detector Based on Neural Networks
inferredcites →https://doi.org/10.1023/a:1015596518147openalex-snapshot
Predicting Weed Species Occurrence Based on Site Properties and Previous Year's Weed Presence
inferredcites →https://doi.org/10.1023/a:1015674004201openalex-snapshot
An Agricultural Mobile Robot with Vision-Based Perception for Mechanical Weed Control
inferredcites →https://doi.org/10.1023/a:1024988022674openalex-snapshot
The Economic Impact of Site-Specific Weed Control
inferredcites →https://doi.org/10.1046/j.1365-3180.2003.00344.xopenalex-snapshot
A decision algorithm for patch spraying
inferredcites →https://doi.org/10.1046/j.1365-3180.2003.00349.xopenalex-snapshot
Real‐time weed detection, decision making and patch spraying in maize, sugarbeet, winter wheat and winter barley
inferredcites →https://doi.org/10.1051/agro:19990701openalex-snapshot
Ultraviolet-induced fluorescence for plant monitoring: present state and prospects
inferredcites →https://doi.org/10.1063/1.3697858openalex-snapshot
Design and evaluation of an imaging spectrophotometer incorporating a uniform light source
inferredcites →https://doi.org/10.1071/fp09095openalex-snapshot
Simultaneous phenotyping of leaf growth and chlorophyll fluorescence via GROWSCREEN FLUORO allows detection of stress tolerance in Arabidopsis thaliana and other rosette plants
inferredcites →https://doi.org/10.1080/00103620701549157openalex-snapshot
Comparison of Ground‐Based Remote Sensors for Evaluation of Corn Biomass Affected by Nitrogen Stress
inferredcites →https://doi.org/10.1080/01431160210163074openalex-snapshot
Vegetation indices derived from high-resolution airborne videography for precision crop management
inferredcites →https://doi.org/10.1080/01431160903258217openalex-snapshot
Characterizing vegetation indices derived from active and passive sensors
inferredcites →https://doi.org/10.1080/014311697217558openalex-snapshot
Remote estimation of chlorophyll content in higher plant leaves
inferredcites →https://doi.org/10.1088/1464-4258/10/10/104020openalex-snapshot
Passive field reflectance measurements
inferredcites →https://doi.org/10.1093/jxb/erp156openalex-snapshot
Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence
inferredcites →https://doi.org/10.1109/igarss.2002.1026212openalex-snapshot
Hyperspectral remote sensing for invasive species detection and mapping
inferredcites →https://doi.org/10.1109/tencon.2010.5686770openalex-snapshot
Optimal feature selection for SVM based weed classification via visual analysis
inferredcites →https://doi.org/10.1111/j.1365-3180.1988.tb01606.xopenalex-snapshot
Field‐scale estimates of grass weed populations in arable land
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.1365-3180.2008.00682.xopenalex-snapshot
Real‐time vision‐based detection of Rumex obtusifolius in grassland
inferredcites →https://doi.org/10.1111/j.1365-3180.2009.00696.xopenalex-snapshot
Site‐specific weed control technologies
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/10.1111/wre.12006openalex-snapshot
Discrimination of A mbrosia artemisiifoliaand A rtemisia vulgarisby hyperspectral image analysis during the growing season
inferredcites →https://doi.org/10.1146/annurev.pp.42.060191.001525openalex-snapshot
Chlorophyll Fluorescence and Photosynthesis: The Basics
inferredcites →https://doi.org/10.13031/2013.17244openalex-snapshot
TEXTURAL IMAGING AND DISCRIMINANT ANALYSIS FOR DISTINGUISHINGWEEDS FOR SPOT SPRAYING
inferredcites →https://doi.org/10.13031/2013.17721openalex-snapshot
HERBICIDE MICRO-DOSING FOR WEED CONTROL IN FIELD-GROWN PROCESSING TOMATOES
inferredcites →https://doi.org/10.13031/2013.22279openalex-snapshot
Ground-Based Sensing System for Cotton Nitrogen Status Determination
inferredcites →https://doi.org/10.13031/2013.27838openalex-snapshot
Color Indices for Weed Identification Under Various Soil, Residue, and Lighting Conditions
inferredcites →https://doi.org/10.13031/2013.27839openalex-snapshot
Shape Features for Identifying Young Weeds Using Image Analysis
inferredcites →https://doi.org/10.13031/2013.27914openalex-snapshot
Effective Criteria for Weed Identification in Wheat Fields Using Machine Vision
inferredcites →https://doi.org/10.13031/2013.31716openalex-snapshot
SHAPE DESCRIPTION OF COMPLETELY VISIBLE AND PARTIALLY OCCLUDED LEAVES FOR IDENTIFYING PLANTS IN DIGITAL IMAGES
inferredcites →https://doi.org/10.13031/2013.39013openalex-snapshot
Ranging Sensors for Vehicle-Based Measurement of Crop Stand and Orchard Parameters: A Review
inferredcites →https://doi.org/10.13031/2013.6995openalex-snapshot
AERIAL CIR REMOTE SENSING FOR WEED DENSITY MAPPING IN A SOYBEAN FIELD
inferredcites →https://doi.org/10.13031/2013.7861openalex-snapshot
PRECISION WEED CONTROL SYSTEM FOR COTTON
inferredcites →https://doi.org/10.13031/2013.8513openalex-snapshot
USE OF AIRBORNE MULTISPECTRAL IMAGERY FOR WEED DETECTION IN FIELD CROPS
inferredcites →https://doi.org/10.1364/ao.24.000074openalex-snapshot
Laser-induced fluorescence of green plants 3: LIF spectral signatures of five major plant types
inferredcites →https://doi.org/10.15488/7934openalex-snapshot
Active shape models with focus on overlapping problems applied to plant detection and soil pore analysis
inferredcites →https://doi.org/10.1614/0043-1745(2000)048[0393:urstdw]2.0.co;2openalex-snapshot
Using remote sensing to detect weed infestations inGlycine max
inferredcites →https://doi.org/10.1614/0043-1745(2002)050[0802:iowmlo]2.0.co;2openalex-snapshot
Influence of weed maturity levels on species classification using machine vision
inferredcites →https://doi.org/10.1614/ws-04-068r1openalex-snapshot
Site-specific weed management: sensing requirements— what do we need to see?
inferredcites →https://doi.org/10.1614/wt-07-096.1openalex-snapshot
Postharvest Control of Russian Thistle (Salsola tragus) with a Reduced Herbicide Applicator in The Pacific Northwest
inferredcites →https://doi.org/10.1614/wt-07-104.1openalex-snapshot
Multispectral Machine Vision Identification of Lettuce and Weed Seedlings for Automated Weed Control
inferredcites →https://doi.org/10.1614/wt-d-10-00082.1openalex-snapshot
Reliability of a Visual Recognition System for Detection of Johnsongrass(Sorghum halepense) in Corn
inferredcites →https://doi.org/10.1641/0006-3568(2004)054[0523:uistse]2.0.co;2openalex-snapshot
Using Imaging Spectroscopy to Study Ecosystem Processes and Properties
inferredcites →https://doi.org/10.3390/s110202177openalex-snapshot
Ultrasonic and LIDAR Sensors for Electronic Canopy Characterization in Vineyards: Advances to Improve Pesticide Application Methods
inferredcites →https://doi.org/10.3390/s110302304openalex-snapshot
Accuracy and Feasibility of Optoelectronic Sensors for Weed Mapping in Wide Row Crops
inferredcites →https://doi.org/10.3390/s110706656openalex-snapshot
Geosensors to Support Crop Production: Current Applications and User Requirements
inferredcites →https://doi.org/10.3390/s121217343openalex-snapshot
An Ultrasonic System for Weed Detection in Cereal Crops
inferredcites →https://doi.org/10.3390/s130201523openalex-snapshot
Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems
inferredcites →https://doi.org/10.3390/s130302830openalex-snapshot
BreedVision — A Multi-Sensor Platform for Non-Destructive Field-Based Phenotyping in Plant Breeding
inferredcites →https://doi.org/10.3390/s8042136openalex-snapshot
Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape
inferredcites →https://doi.org/10.3920/978-90-8686-549-9_076openalex-snapshot
Investigation of the accuracy of a machine vision based robotic micro-spray system
inferredcites →https://doi.org/10.3920/978-90-8686-778-3_6openalex-snapshot
Improving the determination of plant characteristics by fusion of four different sensors
inferredcites →https://doi.org/10.3920/9789086866038_063openalex-snapshot
Image acquisition for weed detection and identification by digital image analysis
inferredcites →https://doi.org/10.5073/jka.2012.434.023openalex-snapshot
Echtzeitregelung der Applikationsmenge bei der Herbizidanwendung mit Hilfe eines Kamerasensors
inferredcites →https://doi.org/10.5073/jka.2012.434.025openalex-snapshot
Precision weed control in sunflower and maize - experiences from Hungary
inferredcites →https://doi.org/10.5772/19983openalex-snapshot
Sensor Fusion for Precision Agriculture
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.4869358openalex-extracted
Weed Identification Using Machine Learning and Deep Learning: A Review
inferred← citeshttps://doi.org/10.1002/9781119709763.ch13openalex-snapshot
Ecologically Based Weed Management in Vegetable Crops
inferred← citeshttps://doi.org/10.1002/ps.4843openalex-snapshot
Impact of sensor‐controlled variable‐rate fungicide application on yield, senescence and disease occurrence in winter wheat fields
inferred← citeshttps://doi.org/10.1002/ps.5630openalex-snapshot
Pre‐planting weed detection based on ground field spectral data
inferred← citeshttps://doi.org/10.1002/ps.6333openalex-snapshot
Increasing the value and efficiency of herbicide resistance surveys
inferred← citeshttps://doi.org/10.1002/ps.6656openalex-snapshot
Evaluation of different deep convolutional neural networks for detection of broadleaf weed seedlings in wheat
inferred← citeshttps://doi.org/10.1002/ps.7102openalex-snapshot
A deep learning‐based method for classification, detection, and localization of weeds in turfgrass
inferred← citeshttps://doi.org/10.1007/978-3-030-44402-0_7openalex-snapshot
Site-Specific Based Models
inferred← citeshttps://doi.org/10.1007/978-3-030-70400-1_6openalex-snapshot
Crop Sensing and Its Application in Precision Agriculture and Crop Phenotyping
inferred← citeshttps://doi.org/10.1007/978-3-030-78431-7_10openalex-snapshot
Sensing for Weed Detection
inferred← citeshttps://doi.org/10.1007/978-3-030-84760-9_44openalex-snapshot
Detection of Weed Plants Using Image Processing and Deep Learning Techniques
inferred← citeshttps://doi.org/10.1007/978-3-031-81669-7_10openalex-snapshot
Technological Innovations Aimed at Reducing the Environmental Impact of Pesticides and Increasing the Resilience of Agriculture to Climate Change
inferred← citeshttps://doi.org/10.1007/978-3-031-84802-5_15openalex-snapshot
Innovative Techniques for Climate-Resilient Crop Production in Protected Environments
inferred← citeshttps://doi.org/10.1007/978-3-031-96534-0_5openalex-snapshot
Weed Management—Identification and Treatment
inferred← citeshttps://doi.org/10.1007/978-981-19-8113-5_19openalex-snapshot
Development of a Recognition System for Spraying Areas from Unmanned Aerial Vehicles Using a Machine Learning Approach
inferred← citeshttps://doi.org/10.1007/s10343-015-0352-2openalex-snapshot
Identifizierung von Beifußblättriger Ambrosie (Ambrosia artemisiifolia) mittels Bildverarbeitung in einem Winterroggenfeld
inferred← citeshttps://doi.org/10.1007/s10343-022-00799-9openalex-snapshot
Arbeitstagung „Sensorgestützte Erkennung von Schaderregern in Freilandkulturen“ am Leibniz-Institut für Agrartechnik und Bioökonomie Potsdam-Bornim (ATB), 11. und 12. Mai 2022
inferred← citeshttps://doi.org/10.1007/s10980-017-0516-9openalex-snapshot
Why non-native grasses pose a critical emerging threat to biodiversity conservation, habitat connectivity and agricultural production in multifunctional rural landscapes
inferred← citeshttps://doi.org/10.1007/s11056-025-10113-wopenalex-snapshot
Use of hyperspectral sensor and random forest for broadleaf and narrowleaf weed differentiation
inferred← citeshttps://doi.org/10.1007/s11119-019-09691-5openalex-snapshot
A new method to estimate the spatial correlation between planned and actual patch spraying of herbicides
inferred← citeshttps://doi.org/10.1007/s11119-026-10409-7openalex-snapshot
The economic viability of spot-spraying for pesticides: the case of Northwest Germany
inferred← citeshttps://doi.org/10.1007/s12524-023-01782-1openalex-snapshot
Detection and Analysis of Weed Impact on Sugar Beet Crop Using Drone Imagery
inferred← citeshttps://doi.org/10.1007/s13762-024-05848-6openalex-snapshot
Generation of maps to localized herbicide application using aerial imaging aerial imaging
inferred← citeshttps://doi.org/10.1007/s41348-025-01209-8openalex-snapshot
Automatic weed detection in paddy field: a review
inferred← citeshttps://doi.org/10.1016/b978-0-12-818617-6.00017-2openalex-snapshot
High-precision GNSS for agricultural operations
inferred← citeshttps://doi.org/10.1016/bs.agron.2019.08.004openalex-snapshot
Unmanned aircraft systems for precision weed detection and management: Prospects and challenges
inferred← citeshttps://doi.org/10.1016/j.atech.2025.101405openalex-snapshot
Advances on deep learning for proximal image-based weed recognition and control under authentic farmlands: A state-of-the-art review
inferred← citeshttps://doi.org/10.1016/j.biosystemseng.2019.11.023openalex-snapshot
Spectral differentiation of sugarcane from weeds
inferred← citeshttps://doi.org/10.1016/j.compag.2015.06.001openalex-snapshot
Evaluation of sensors for poplar cutting detection to be used in intra-row weed control machine
inferred← citeshttps://doi.org/10.1016/j.compag.2015.10.011openalex-snapshot
LiDAR: An important tool for next-generation phenotyping technology of high potential for plant phenomics?
inferred← citeshttps://doi.org/10.1016/j.compag.2017.05.018openalex-snapshot
Controlled comparison of machine vision algorithms for Rumex and Urtica detection in grassland
inferred← citeshttps://doi.org/10.1016/j.compag.2019.01.007openalex-snapshot
Aerial imagery or on-ground detection? An economic analysis for vineyard crops
inferred← citeshttps://doi.org/10.1016/j.compag.2019.02.005openalex-snapshot
A review on weed detection using ground-based machine vision and image processing techniques
inferred← citeshttps://doi.org/10.1016/j.compag.2020.105638openalex-snapshot
Sensor-based mechanical weed control: Present state and prospects
inferred← citeshttps://doi.org/10.1016/j.compag.2022.106881openalex-snapshot
Hyperspectral imaging facilitates early detection of Orobanche cumana below-ground parasitism on sunflower under field conditions
inferred← citeshttps://doi.org/10.1016/j.compag.2023.107753openalex-snapshot
Assessment of map based variable rate strategies for copper reduction in hedge vineyards
inferred← citeshttps://doi.org/10.1016/j.compag.2023.108419openalex-snapshot
Investigating image-based fallow weed detection performance on Raphanus sativus and Avena sativa at speeds up to 30 km h−1
inferred← citeshttps://doi.org/10.1016/j.compag.2025.111067openalex-snapshot
Conflict avoidance task planning strategy for dual-arm cooperative strawberry harvesting robots
inferred← citeshttps://doi.org/10.1016/j.compag.2025.111167openalex-snapshot
Recent developments and applications of weed detection, invasion prediction and early warning: A review
inferred← citeshttps://doi.org/10.1016/j.compag.2025.111219openalex-snapshot
3D sensing and perception for precision weed management: a review of modalities, reconstruction pipelines, and context-aware detection
inferred← citeshttps://doi.org/10.1016/j.cropro.2023.106302openalex-snapshot
Precision weed control using a smart sprayer in dormant bermudagrass turf
inferred← citeshttps://doi.org/10.1016/j.cropro.2025.107320openalex-snapshot
Current status of herbicide resistance in global cotton production: trends and perspectives
inferred← citeshttps://doi.org/10.1016/j.eja.2015.11.026openalex-snapshot
Are vegetation indices derived from consumer-grade cameras mounted on UAVs sufficiently reliable for assessing experimental plots?
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2015.03.003openalex-snapshot
Comparative classification analysis of post-harvest growth detection from terrestrial LiDAR point clouds in precision agriculture
inferred← citeshttps://doi.org/10.1016/j.jafr.2025.102516openalex-snapshot
Review of current robotic approaches for weed management in paddy cultivation
inferred← citeshttps://doi.org/10.1017/wet.2022.84openalex-snapshot
Weed detection to weed recognition: reviewing 50 years of research to identify constraints and opportunities for large-scale cropping systems
inferred← citeshttps://doi.org/10.1017/wsc.2022.64openalex-snapshot
Early and on-ground image-based detection of poppy (Papaver rhoeas) in wheat using YOLO architectures
inferred← citeshttps://doi.org/10.1038/s41598-021-03858-9openalex-snapshot
OpenWeedLocator (OWL): an open-source, low-cost device for fallow weed detection
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/10.1079/9781789249170.0006openalex-snapshot
Competitive Ecology and Sustainable Production
inferred← citeshttps://doi.org/10.1080/01431161.2017.1410300openalex-snapshot
What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture?
inferred← citeshttps://doi.org/10.1080/09583157.2016.1209161openalex-snapshot
Weed biocontrol with fungi: past, present and future
inferred← citeshttps://doi.org/10.1080/09593330.2018.1498923openalex-snapshot
Elucidation of 2, 4-Dichlorophenol degradation by Bacillus licheniformis strain SL10
inferred← citeshttps://doi.org/10.1080/15592324.2019.1581558openalex-snapshot
Use of a visible reporter marker- myb -related gene in crop plants to minimize herbicide usage against weeds
inferred← citeshttps://doi.org/10.1109/access.2024.3418454openalex-snapshot
Deep Learning Techniques for Weed Detection in Agricultural Environments: A Comprehensive Review
inferred← citeshttps://doi.org/10.1109/cac53003.2021.9727999openalex-snapshot
Maize Seedling and Weed Detection based on MobileNetv3-YOLOv4
inferred← citeshttps://doi.org/10.1109/iot-siu.2019.8777646openalex-snapshot
An experimental set up for utilizing convolutional neural network in automated weed detection
inferred← citeshttps://doi.org/10.1109/tase.2017.2656143openalex-snapshot
Automatic Adjustable Spraying Device for Site-Specific Agricultural Application
inferred← citeshttps://doi.org/10.1111/gfs.12583openalex-snapshot
Drought stress impact on the performance of deep convolutional neural networks for weed detection in Bahiagrass
inferred← citeshttps://doi.org/10.1111/wre.12205openalex-snapshot
Real‐time variable‐rate herbicide application for weed control in carrots
inferred← citeshttps://doi.org/10.1111/wre.12307openalex-snapshot
Is the current state of the art of weed monitoring suitable for site‐specific weed management in arable crops?
inferred← citeshttps://doi.org/10.1111/wre.12469openalex-snapshot
Site‐specific weed management—constraints and opportunities for the weed research community: Insights from a workshop
inferred← citeshttps://doi.org/10.1111/wre.12526openalex-snapshot
Advances in site‐specific weed management in agriculture—A review
inferred← citeshttps://doi.org/10.1111/wre.70037openalex-snapshot
Laser Weeding Technology: A Promising Sustainable Weed Control Method
inferred← citeshttps://doi.org/10.1145/3488933.3488971openalex-snapshot
Semantic-guided Image Feature Matching for Agricultural Robots
inferred← citeshttps://doi.org/10.11606/d.11.2023.tde-12042024-144022openalex-snapshot
Imageamento aéreo para aplicação localizada de herbicidas
inferred← citeshttps://doi.org/10.11648/j.ijssn.20241201.12openalex-snapshot
Indoor Positioning of AGVs Based on Multi-Sensor Data Fusion Such as LiDAR
inferred← citeshttps://doi.org/10.1177/09544062251327820openalex-snapshot
Impact of nodal characteristics, moisture content, and position section on the quasistatic and dynamic mechanical strength of sorghum stalks ( Sorghum bicolor (L.) Moench )
inferred← citeshttps://doi.org/10.1201/9780429266737openalex-snapshot
Robotics and automation for improving agriculture
inferred← citeshttps://doi.org/10.15150/lt.2015.2657openalex-snapshot
Zielflächenorientierte, präzise Echtzeit-Fungizidapplikation in Getreide
inferred← citeshttps://doi.org/10.1614/ws-d-15-00117.1openalex-snapshot
Diverse Approaches to Herbicide-Resistant Weed Management
inferred← citeshttps://doi.org/10.1614/wt-d-16-00039.1openalex-snapshot
Weed Decision Threshold as a Key Factor for Herbicide Reductions in Site-Specific Weed Management
inferred← citeshttps://doi.org/10.17221/76/2024-ppsopenalex-snapshot
Advancements in sensor-based weed management: Navigating the future of weed control
inferred← citeshttps://doi.org/10.17485/ijst/2019/v12i48/149410openalex-snapshot
A Review on Weed Detection Using Image Processing
inferred← citeshttps://doi.org/10.17762/turcomat.v12i1s.1559openalex-snapshot
An automatic pesticide sprayer to detect the crop disease using machine learning algorithms and spraying pesticide on affected crops
inferred← citeshttps://doi.org/10.18174/423464openalex-snapshot
Geintegreerde bestrijding van knolcyperus : Resultaten van een literatuurstudie naar alternatieven voor monam
inferred← citeshttps://doi.org/10.18174/442084openalex-snapshot
Precisietechnologie Tuinbouw: PPS Autonoom onkruid verwijderen : D2.4 Literatuurstudie spectrale reflectie-eigenschappen van planten en onkruiden; D2.5 Lab en veldexperimenten spectrale reflectie-eigenschappen van planten en onkruiden
inferred← citeshttps://doi.org/10.20868/upm.thesis.66974openalex-snapshot
Optical sensors for crop monitoring – From 2D to 3D reconstruction
inferred← citeshttps://doi.org/10.2139/ssrn.5258564openalex-snapshot
Task Planning for a Dual-Arm Cooperative Strawberry Harvesting Robot
inferred← citeshttps://doi.org/10.2139/ssrn.6864585openalex-snapshot
EAGLE-YOLO: An edge-aware lightweight detector for real-time maize seedling detection in robotic intra-row weeding
inferred← citeshttps://doi.org/10.21475/ajcs.2016.10.09.p6661openalex-snapshot
Development and testing of image processing algorithm to estimate weed infestation level in corn fields
inferred← citeshttps://doi.org/10.26480/rfna.02.2023.45.49openalex-snapshot
PRECISION AGRICULTURE: REVIEWING THE ADVANCEMENTS, TECHNOLOGIES, AND APPLICATIONS IN PRECISION AGRICULTURE FOR IMPROVED CROP PRODUCTIVITY AND RESOURCE MANAGEMENT
inferred← citeshttps://doi.org/10.31390/gradschool_theses.5228openalex-snapshot
Within-Field Yield Prediction for Sugarcane and Rice Focused on Precision Agriculture Applications
inferred← citeshttps://doi.org/10.31727/gzb.46.5.4openalex-snapshot
Automatska kontrola rada prskalice
inferred← citeshttps://doi.org/10.33545/2618060x.2024.v7.i4sa.509openalex-snapshot
Advancements in precision control in intra-row weeding: A comprehensive review
inferred← citeshttps://doi.org/10.3389/fpls.2023.1351481openalex-snapshot
Editorial: Weed identification and integrated control
inferred← citeshttps://doi.org/10.3390/agriculture10080362openalex-snapshot
Latest Advances in Sensor Applications in Agriculture
inferred← citeshttps://doi.org/10.3390/agriculture12101541openalex-snapshot
Weed Detection in Peanut Fields Based on Machine Vision
inferred← citeshttps://doi.org/10.3390/agriculture15161787openalex-snapshot
Active Chlorophyll Fluorescence Technologies in Precision Weed Management: Overview and Perspectives
inferred← citeshttps://doi.org/10.3390/agriculture6020024openalex-snapshot
Using Optical Sensors to Identify Water Deprivation, Nitrogen Shortage, Weed Presence and Fungal Infection in Wheat
inferred← citeshttps://doi.org/10.3390/agriculture9010018openalex-snapshot
Development of an Autonomous Electric Robot Implement for Intra-Row Weeding in Vineyards
inferred← citeshttps://doi.org/10.3390/agronomy10040452openalex-snapshot
Spatial and Temporal Stability of Weed Patches in Cereal Fields under Direct Drilling and Harrow Tillage
inferred← citeshttps://doi.org/10.3390/agronomy11081517openalex-snapshot
Sensor-Based Intrarow Mechanical Weed Control in Sugar Beets with Motorized Finger Weeders
inferred← citeshttps://doi.org/10.3390/agronomy11102084openalex-snapshot
Efficacy of Various Mechanical Weeding Methods—Single and in Combination—In Terms of Different Field Conditions and Weed Densities
inferred← citeshttps://doi.org/10.3390/agronomy11112277openalex-snapshot
The Predictive Power of Regression Models to Determine Grass Weed Infestations in Cereals Based on Drone Imagery—Statistical and Practical Aspects
inferred← citeshttps://doi.org/10.3390/agronomy12051091openalex-snapshot
Non-Chemical Weed Control for Plant Health and Environment: Ecological Integrated Weed Management (EIWM)
inferred← citeshttps://doi.org/10.3390/agronomy12122953openalex-snapshot
Intelligent Weed Management Based on Object Detection Neural Networks in Tomato Crops
inferred← citeshttps://doi.org/10.3390/agronomy13071878openalex-snapshot
Looking beyond Glyphosate for Site-Specific Fallow Weed Control in Australian Grain Production
inferred← citeshttps://doi.org/10.3390/agronomy13082069openalex-snapshot
Back to the Future: What Is Trending on Precision Agriculture?
inferred← citeshttps://doi.org/10.3390/agronomy14112649openalex-snapshot
A Lightweight Cotton Field Weed Detection Model Enhanced with EfficientNet and Attention Mechanisms
inferred← citeshttps://doi.org/10.3390/app122311935openalex-snapshot
A Simple Method to Estimate Weed Control Threshold by Using RGB Images from Drones
inferred← citeshttps://doi.org/10.3390/ijgi4010385openalex-snapshot
A Sensor Web-Enabled Infrastructure for Precision Farming
inferred← citeshttps://doi.org/10.3390/jimaging1010115openalex-snapshot
Precise Navigation of Small Agricultural Robots in Sensitive Areas with a Smart Plant Camera
inferred← citeshttps://doi.org/10.3390/jimaging3010009openalex-snapshot
3D Imaging with a Sonar Sensor and an Automated 3-Axes Frame for Selective Spraying in Controlled Conditions
inferred← citeshttps://doi.org/10.3390/rs12142229openalex-snapshot
Application of Color Featuring and Deep Learning in Maize Plant Detection
inferred← citeshttps://doi.org/10.3390/rs12244040openalex-snapshot
Spectrum- and RGB-D-Based Image Fusion for the Prediction of Nitrogen Accumulation in Wheat
inferred← citeshttps://doi.org/10.3390/rs12244185openalex-snapshot
Weed Identification in Maize, Sunflower, and Potatoes with the Aid of Convolutional Neural Networks
inferred← citeshttps://doi.org/10.3390/rs13050943openalex-snapshot
Hair Fescue and Sheep Sorrel Identification Using Deep Learning in Wild Blueberry Production
inferred← citeshttps://doi.org/10.3390/rs15215165openalex-snapshot
Transformer in UAV Image-Based Weed Mapping
inferred← citeshttps://doi.org/10.3390/s151129346openalex-snapshot
An Analytic Model for the Success Rate of a Robotic Actuator System in Hitting Random Targets
inferred← citeshttps://doi.org/10.3390/s18092931openalex-snapshot
Evaluating RGB Imaging and Multispectral Active and Hyperspectral Passive Sensing for Assessing Early Plant Vigor in Winter Wheat
inferred← citeshttps://doi.org/10.3390/s19020313openalex-snapshot
Development of a Recognition System for Spraying Areas from Unmanned Aerial Vehicles Using a Machine Learning Approach
inferred← citeshttps://doi.org/10.3390/s19030535openalex-snapshot
Comparing UAV-Based Technologies and RGB-D Reconstruction Methods for Plant Height and Biomass Monitoring on Grass Ley
inferred← citeshttps://doi.org/10.3390/s19071569openalex-snapshot
3-D Image-Driven Morphological Crop Analysis: A Novel Method for Detection of Sunflower Broomrape Initial Subsoil Parasitism
inferred← citeshttps://doi.org/10.3390/s19132883openalex-snapshot
Low-Cost Three-Dimensional Modeling of Crop Plants
inferred← citeshttps://doi.org/10.3390/s20071830openalex-snapshot
Measurement Method for Height-Independent Vegetation Indices Based on an Active Light Source
inferred← citeshttps://doi.org/10.3390/s20236912openalex-snapshot
Evaluation of Vineyard Cropping Systems Using On-Board RGB-Depth Perception
inferred← citeshttps://doi.org/10.3390/s21113647openalex-snapshot
Review of Weed Detection Methods Based on Computer Vision
inferred← citeshttps://doi.org/10.3390/s22249723openalex-snapshot
Evaluation of a CNN-Based Modular Precision Sprayer in Broadcast-Seeded Field
inferred← citeshttps://doi.org/10.3390/s24206743openalex-snapshot
Sensing and Perception in Robotic Weeding: Innovations and Limitations for Digital Agriculture
inferred← citeshttps://doi.org/10.3390/s25185670openalex-snapshot
Research on Multi-Sensor Fusion Localization for Forklift AGV Based on Adaptive Weight Extended Kalman Filter
inferred← citeshttps://doi.org/10.3390/su142215088openalex-snapshot
Real-Time Detection of Seedling Maize Weeds in Sustainable Agriculture
inferred← citeshttps://doi.org/10.3390/su15031843openalex-snapshot
Artificial Intelligence Tools and Techniques to Combat Herbicide Resistant Weeds—A Review
inferred← citeshttps://doi.org/10.35633/inmateh-74-14openalex-snapshot
DESIGN AND DEVELOPMENT OF SUNFLOWER INTELLIGENT INSERTION TRAY DRYER
inferred← citeshttps://doi.org/10.3920/978-90-8686-814-8_70openalex-snapshot
Using sensors to assess herbicide stress in sugar beet
inferred← citeshttps://doi.org/10.4018/978-1-6684-6413-7.ch001openalex-snapshot
Digital Technologies and Tools for the Ensuing Digital Era
inferred← citeshttps://doi.org/10.4236/mi.2017.61001openalex-snapshot
Mobile Open-Source Plant-Canopy Monitoring System
inferred← citeshttps://doi.org/10.47749/t/unicamp.2018.998893openalex-snapshot
Mapeamento de infestações de plantas daninhas em lavouras de cana-de-açúcar por aeronave remotamente pilotada (RPA)
inferred← citeshttps://doi.org/10.54254/2755-2721/79/20241588openalex-snapshot
A review of decision-making frameworks for autonomous vehicles
inferred← citeshttps://doi.org/10.55041/ijsrem30722openalex-snapshot
AI Driven Applications for Precision Weed Management in Agricultural Crops
inferred← citeshttps://doi.org/10.5935/1806-6690.20200086openalex-snapshot
Sensors Applied to Digital Agriculture: A Review
inferred← citeshttps://doi.org/10.5935/1806-6690.20200100openalex-snapshot
Agro 4.0: Enabling agriculture digital transformation through IoT
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.