Research graph
References from UAV remote sensing for crop lodging monitoring: A comprehensive review. Local targets link to admitted publications; unresolved targets remain external evidence.
Smart farming using artificial intelligence: a review
10.1016/j.engappai.2023.105899 · 2023 · External reference
LodgeNet: an automated framework for precise detection and classification of wheat lodging severity levels in precision farming
10.3389/fpls.2023.1255961 · 2023 · External reference
Impact of climate change on agriculture production and its sustainable solutions
10.1007/s42398-019-00078-w · 2019 · External reference
Comprehensive wheat lodging detection after initial lodging using UAV RGB images
10.1016/j.eswa.2023.121788 · 2024 · External reference
Estimation of soybean yield parameters under lodging conditions using RGB information from unmanned aerial vehicles
10.3389/fpls.2022.1012293 · 2022 · External reference
A method for the assessment of the risk of wheat lodging
10.1006/jtbi.1998.0778 · 1998 · External reference
A generalised model of crop lodging
10.1016/j.jtbi.2014.07.032 · 2014 · External reference
Development and application of a model for calculating the risk of stem and root lodging in maize
10.1016/j.fcr.2020.108037 · 2021 · External reference
Predicting yield losses caused by lodging in wheat
10.1016/j.fcr.2012.07.019 · 2012 · External reference
A comparison of root and stem lodging risks among winter wheat cultivars
10.1017/s002185960300354x · 2003 · External reference
Understanding and reducing lodging in cereals
2004 · External reference
Damage assessment due to wheat lodging using UAV-based multispectral and thermal imageries
10.1007/s12524-023-01680-6 · 2023 · External reference
Timely assessment of maize lodging severity with limited samples using multi-temporal Sentinel-1 and Sentinel-2 data across large spatial extents
10.1016/j.compag.2025.110671 · 2025 · External reference
Use of unmanned aerial vehicle imagery and a hybrid algorithm combining a watershed algorithm and adaptive threshold segmentation to extract wheat lodging
10.1016/j.pce.2021.103016 · 2021 · External reference
Estimation of crop angle of inclination for lodged wheat using multi-sensor SAR data
10.1016/j.rse.2019.111488 · 2020 · External reference
Discriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data
10.1016/j.isprsjprs.2020.04.012 · 2020 · External reference
Remote sensing-based crop lodging assessment: current status and perspectives
10.1016/j.isprsjprs.2019.03.005 · 2019 · External reference
Understanding wheat lodging using multi-temporal Sentinel-1 and Sentinel-2 data
10.1016/j.rse.2020.111804 · 2020 · External reference
Mapping of wheat lodging susceptibility with synthetic aperture radar data
10.1016/j.rse.2021.112427 · 2021 · External reference
UAV remote sensing imagery-based semantic segmentation approach for lodged rice region
2025 · External reference
Methods and datasets on semantic segmentation for unmanned aerial vehicle remote sensing images: a review
10.1016/j.isprsjprs.2024.03.012 · 2024 · External reference
A decision-tree approach to identifying paddy rice lodging with multiple pieces of polarization information derived from Sentinel-1
10.3390/rs15010240 · 2022 · External reference
Segmentation of wheat lodging areas from UAV imagery using an ultra-lightweight network
10.3390/agriculture14020244 · 2024 · External reference
RTAL: an edge computing method for real-time rice lodging assessment
10.1016/j.compag.2023.108386 · 2023 · External reference
Food security: the challenge of feeding 9 billion people
10.1126/science.1185383 · 2010 · External reference
A novel approach to estimate maize lodging area with PolSAR data
2022 · External reference
An improved approach to estimating crop lodging percentage with Sentinel-2 imagery using machine learning
2022 · External reference
A quantitative monitoring method for determining maize lodging in different growth stages
10.3390/rs12193149 · 2020 · External reference
SWRD-YOLO: a lightweight instance segmentation model for estimating rice lodging degree in UAV remote sensing images with real-time edge deployment
10.3390/agriculture15151570 · 2025 · External reference
Automatic detection of crop lodging from multitemporal satellite data based on the isolation forest algorithm
10.1016/j.compag.2023.108415 · 2023 · External reference
SegNeXt-RCMSCA: an improved SegNeXt network for detecting winter wheat lodging from UAS RGB images
2025 · External reference
What’s next in agri-vision: a review of Vision Transformers and Vision Mamba in crop management
10.1016/j.compag.2026.111551 · 2026 · External reference
Quantitative identification of maize lodging-causing feature factors using unmanned aerial vehicle images and a nomogram computation
10.3390/rs10101528 · 2018 · External reference
An explainable XGBoost model improved by SMOTE-ENN technique for maize lodging detection based on multi-source unmanned aerial vehicle images
10.1016/j.compag.2022.106804 · 2022 · External reference
Review of synthetic aperture radar with deep learning in agricultural applications
10.1016/j.isprsjprs.2024.08.018 · 2024 · External reference
Comparison of the performance of multi-source three-dimensional structural data in the application of monitoring maize lodging
10.1016/j.compag.2023.107782 · 2023 · External reference
Assessing the self-recovery ability of maize after lodging using UAV-LiDAR data
10.3390/rs13122270 · 2021 · External reference
Identifying key factors influencing maize stalk lodging resistance through wind tunnel simulations with machine learning algorithms
2025 · External reference
Radar taking off: New capabilities for UAVs
10.1109/mmm.2018.2862558 · 2018 · External reference
State-of-the-art and future research challenges in UAV swarms
10.1109/jiot.2024.3364230 · 2024 · External reference
UAV-satellite synergies for crop monitoring: current landscape, challenges, and future directions
10.1016/j.isprsjprs.2026.06.038 · 2026 · External reference
Monitoring wheat lodging at various growth stages
10.3390/s22186967 · 2022 · External reference
Automated calculation of rice-lodging rates within a parcel area in a mobile environment using aerial imagery
10.3390/rs18010021 · 2025 · External reference
Deep learning in agriculture: a survey
10.1016/j.compag.2018.02.016 · 2018 · External reference
Lightweight detection system with global attention network (gloan) for rice lodging
10.3390/plants12081595 · 2023 · External reference
Analysis of changes in rice yield components and vegetation indices in response to lodging timing during the grain-filling stage, lodging severity, and nitrogen fertilization
10.1007/s12892-025-00313-3 · 2025 · External reference
Segment anything
2023 · External reference
Prediction of areal soybean lodging using a main stem elongation model and a soil-adjusted vegetation index that accounts for the ratio of vegetation cover
10.3390/rs15133446 · 2023 · External reference
Machine learning based plot level rice lodging assessment using multi-spectral UAV remote sensing
10.1016/j.compag.2024.108754 · 2024 · External reference
Extraction of sunflower lodging information based on UAV multi-spectral remote sensing and deep learning
10.3390/rs13142721 · 2021 · External reference
A review on enhancing agricultural intelligence with large language models
2025 · External reference
Foundation models in smart agriculture: Basics, opportunities, and challenges
10.1016/j.compag.2024.109032 · 2024 · External reference
A UAV-based framework for crop lodging assessment
10.1016/j.eja.2020.126201 · 2021 · External reference
Vision-language models in remote sensing: current progress and future trends
10.1109/mgrs.2024.3383473 · 2024 · External reference
Identification lodging degree of wheat using point cloud data and convolutional neural network
2022 · External reference
Unmanned aerial vehicles (UAVs)-based crop lodging susceptibility and seed yield assessment during different growth stages of rapeseed (Brassica napus)
10.1016/j.compag.2024.108980 · 2024 · External reference
Winter wheat weed detection based on deep learning models
10.1016/j.compag.2024.109448 · 2024 · External reference
Quantification of root lodging damage in corn using uncrewed aerial vehicle imagery
10.1002/cft2.20241 · 2023 · External reference
Estimates of rice lodging using indices derived from UAV visible and thermal infrared images
10.1016/j.agrformet.2018.01.021 · 2018 · External reference
Highly efficient wheat lodging extraction algorithm based on two-peak search algorithm
10.1007/s11119-025-10223-7 · 2025 · External reference
Evaluating how lodging affects maize yield estimation based on UAV observations
10.3389/fpls.2022.979103 · 2023 · External reference
Comprehensive wheat lodging detection under different UAV heights using machine/deep learning models
10.1016/j.compag.2025.109972 · 2025 · External reference
Perspectives for remote sensing with unmanned aerial vehicles in precision agriculture
10.1016/j.tplants.2018.11.007 · 2019 · External reference
Applications of UAV thermal imagery in precision agriculture: State of the art and future research outlook
10.3390/rs12091491 · 2020 · External reference
UAS-borne radar for remote sensing: a review
10.3390/electronics11203324 · 2022 · External reference
A tutorial on synthetic aperture radar
10.1109/mgrs.2013.2248301 · 2013 · External reference
Unmanned Aerial Vehicles (UAVs) for smart agriculture with machine learning: a system-oriented review of methods, applications, and challenges
2026 · External reference
Tracking the impact of typhoons on maize growth and recovery using Sentinel-1 and Sentinel-2 data: a case study of Northeast China
10.1016/j.agrformet.2024.110266 · 2024 · External reference
A survey of unmanned aerial sensing solutions in precision agriculture
10.1016/j.jnca.2019.102461 · 2019 · External reference
Lodging prevention in cereals: Morphological, biochemical, anatomical traits and their molecular mechanisms, management and breeding strategies
10.1016/j.fcr.2022.108733 · 2022 · External reference
Real-time UAV-based wheat lodging detection via edge-accelerated improved Mask-RT-DETR
2025 · External reference
UAV-based LiDAR and multispectral imaging for estimating dry bean plant height, lodging and seed yield
10.3390/s25113535 · 2025 · External reference
Lodging in wheat, barley, and oats: the phenomenon, its causes, and preventive measures
10.1016/s0065-2113(08)60782-8 · 1974 · External reference
Monitoring lodging extents of maize crop using multitemporal GF-1 images. IEEE J
2022 · External reference
Monitoring maize lodging severity based on multi-temporal Sentinel-1 images using Time-weighted Dynamic time Warping
10.1016/j.compag.2023.108365 · 2023 · External reference
A compilation of UAV applications for precision agriculture
10.1016/j.comnet.2020.107148 · 2020 · External reference
A systematic review of hyperspectral imaging in precision agriculture: Analysis of its current state and future prospects
10.1016/j.compag.2024.109037 · 2024 · External reference
Drones in agriculture: a review and bibliometric analysis
10.1016/j.compag.2022.107017 · 2022 · External reference
Relationship between lodging, morphological characters and yield of varieties of maize (Zea mays L.)
10.1017/s0021859600060019 · 1978 · External reference
Integrating UAV, UGV and UAV-UGV collaboration in future industrialized agriculture: Analysis, opportunities and challenges
10.1016/j.compag.2024.109631 · 2024 · External reference
LiDAR applications in precision agriculture for cultivating crops: a review of recent advances
10.1016/j.compag.2023.107737 · 2023 · External reference
High-resolution image synthesis with latent diffusion models
2022 · External reference
Object detection with multimodal large vision-language models: an in-depth review
10.1016/j.inffus.2025.103575 · 2026 · External reference
10.1109/tase.2025.3612154
10.1109/tase.2025.3612154 · External reference
Assessment of soybean lodging using UAV imagery and machine learning
10.3390/plants12162893 · 2023 · External reference
Lodging reduces yield of rice by self-shading and reductions in canopy photosynthesis
10.1016/s0378-4290(96)01058-1 · 1997 · External reference
Assessing maize lodging severity using multitemporal UAV-based digital images
10.1016/j.eja.2023.126754 · 2023 · External reference
Monitoring of maize lodging using multi-temporal Sentinel-1 SAR data
10.1016/j.asr.2019.09.034 · 2020 · External reference
A research review on deep learning combined with hyperspectral imaging in multiscale agricultural sensing
10.1016/j.compag.2023.108577 · 2024 · External reference
High-throughput phenotyping enabled genetic dissection of crop lodging in wheat
10.3389/fpls.2019.00394 · 2019 · External reference
Identifying sunflower lodging based on image fusion and deep semantic segmentation with UAV remote sensing imaging
10.1016/j.compag.2020.105812 · 2020 · External reference
Radar remote sensing of agricultural canopies: a review
10.1109/jstars.2016.2639043 · 2017 · External reference
AI meets UAVs: a survey on AI empowered UAV perception systems for precision agriculture
10.1016/j.neucom.2022.11.020 · 2023 · External reference
LodgeNet: improved rice lodging recognition using semantic segmentation of UAV high-resolution remote sensing images
10.1016/j.compag.2022.106873 · 2022 · External reference
Bridging the gap between hyperspectral imaging and crop breeding: soybean yield prediction and lodging classification with prototype contrastive learning
10.1016/j.compag.2024.109859 · 2025 · External reference
RL-DeepLabv3+: a lightweight rice lodging semantic segmentation model for unmanned rice harvester
10.1016/j.compag.2023.107823 · 2023 · External reference
Estimation of canopy nitrogen nutrient status in lodging maize using unmanned aerial vehicles hyperspectral data
10.1016/j.ecoinf.2023.102315 · 2023 · External reference
A new comprehensive index for monitoring maize lodging severity using UAV-based multi-spectral imagery
10.1016/j.compag.2022.107362 · 2022 · External reference
Evaluation of growth recovery grade in lodging maize via UAV-based hyperspectral images
10.34133/remotesensing.0253 · 2024 · External reference
Monitoring rice lodging grade via Sentinel-2A images based on change vector analysis
10.1080/01431161.2021.2012293 · 2022 · External reference
Monitoring maize canopy chlorophyll density under lodging stress based on UAV hyperspectral imagery
10.1016/j.compag.2021.106671 · 2022 · External reference
Monitoring maize lodging grades via unmanned aerial vehicle multispectral image
10.34133/2019/5704154 · 2019 · External reference
Assessing rice lodging using UAV visible and multispectral image
10.1080/01431161.2021.1942575 · 2021 · External reference
Utilizing temporal measurements from UAVs to assess root lodging in maize and its impact on productivity
10.1016/j.fcr.2020.108014 · 2021 · External reference
Implementing spatio-temporal 3D-convolution neural networks and UAV time series imagery to better predict lodging damage in sorghum
10.3390/rs14030733 · 2022 · External reference
Determining rapeseed lodging angles and types for lodging phenotyping using morphological traits derived from UAV images
10.1016/j.eja.2024.127104 · 2024 · External reference
UAV environmental perception and autonomous obstacle avoidance: a deep learning and depth camera combined solution
10.1016/j.compag.2020.105523 · 2020 · External reference
A review of deep learning in multiscale agricultural sensing
10.3390/rs14030559 · 2022 · External reference
Farmland obstacle detection from the perspective of UAVs based on non-local deformable DETR
10.3390/agriculture12121983 · 2022 · External reference
Classification of maize lodging types using UAV-SAR remote sensing data and machine learning methods
10.1016/j.compag.2024.109637 · 2024 · External reference
A survey of unmanned aerial vehicles and deep learning in precision agriculture
10.1016/j.eja.2024.127477 · 2025 · External reference
YOLO-EMA: Efficient mamba attention enhanced YOLOv10 for real-time detection and segmentation of winter wheat weeds on edge AI platforms
2026 · External reference
A novel benchmark for rice lodging assessment with X-Band UAV-PolSAR and 3D-RLMamba
10.1016/j.compag.2026.111730 · 2026 · External reference
Classification of rice yield using UAV-based hyperspectral imagery and lodging feature
10.34133/2021/9765952 · 2021 · External reference
UAS-based remote sensing for agricultural monitoring: current status and perspectives
10.1016/j.compag.2024.109501 · 2024 · External reference
A grid-level segmentation model based on encoder-decoder structure with multi-source features for crop lodging detection
10.1016/j.asoc.2023.111113 · 2024 · External reference
Wind-induced response of rapeseed seedling stage and lodging prediction based on UAV imagery and machine learning methods
10.1016/j.compag.2024.108637 · 2024 · External reference
Complementary-aware collaborative fusion: advancing precise wheat lodging mapping using UAV-borne RGB imagery and LiDAR data
10.1016/j.compag.2026.112109 · 2026 · External reference
UAV LiDAR-based automated detection of maize lodging in complex agroecosystems
10.3390/drones9120876 · 2025 · External reference
MSSVT: Multi-branch spatial-spectral volumetric transformer for rice lodging segmentation with UAV multimodal fusion
10.1016/j.compag.2026.112087 · 2026 · External reference
Detection and analysis of degree of maize lodging using UAV-RGB image multi-feature factors and various classification methods
10.3390/ijgi10050309 · 2021 · External reference
Comprehensive risk fine dynamic assessment and zoning of maize high wind lodging disasters in Jilin Province
2025 · External reference
Study on fine early warning of maize high wind lodging disaster risk in Jilin Province
2025 · External reference
Spatial-temporal distribution and hazard assessment of maize lodging in a synergistic disaster environment
10.1016/j.agrformet.2023.109730 · 2023 · External reference
Remote sensing for agricultural applications: a meta-review
10.1016/j.rse.2019.111402 · 2020 · External reference
Quantifying lodging percentage and lodging severity using a UAV-based canopy height model combined with an objective threshold approach
10.3390/rs11050515 · 2019 · External reference
FarmSeg_VLM: a farmland remote sensing image segmentation method considering vision-language alignment
10.1016/j.isprsjprs.2025.05.010 · 2025 · External reference
Soybean lodging classification and yield prediction using multimodal UAV data fusion and deep learning
10.3390/rs17091490 · 2025 · External reference
Accurate wheat lodging extraction from multi-channel UAV images using a lightweight network model
10.3390/s21206826 · 2021 · External reference
Wheat lodging monitoring using polarimetric index from RADARSAT-2 data
2015 · External reference
An integrated strategy coordinating endogenous and exogenous approaches to alleviate crop lodging
10.1016/j.stress.2023.100197 · 2023 · External reference
Adaptive autonomous UAV scouting for rice lodging assessment using edge computing with deep learning EDANet
10.1016/j.compag.2020.105817 · 2020 · External reference
Spatial and spectral hybrid image classification for rice lodging assessment through UAV imagery
10.3390/rs9060583 · 2017 · External reference
Rule-based multi-task deep learning for highly efficient rice lodging segmentation
10.3390/rs17091505 · 2025 · External reference
Semantic segmentation using deep learning with vegetation indices for rice lodging identification in multi-date UAV visible images
10.3390/rs12040633 · 2020 · External reference
Classification of maize lodging extents using deep learning algorithms by UAV-based RGB and multispectral images
10.3390/agriculture12070970 · 2022 · External reference
Wheat lodging extraction using improved_unet network
2022 · External reference
Wheat lodging segmentation based on Lstm_PSPNet deep learning network
10.3390/drones7020143 · 2023 · External reference
Automatic grading evaluation of winter wheat lodging based on deep learning
10.3389/fpls.2024.1284861 · 2024 · External reference
Large-scale wheat lodging monitoring by band transformation of UAV and sentinel-2A multispectral imagery
2026 · External reference
Automatic extraction of wheat lodging area based on transfer learning method and deeplabv3+ network
10.1016/j.compag.2020.105845 · 2020 · External reference
Enhancing model performance in detecting lodging areas in wheat fields using UAV RGB Imagery: considering spatial and temporal variations
10.1016/j.compag.2023.108297 · 2023 · External reference
UssNet: a spatial self-awareness algorithm for wheat lodging area detection
2026 · External reference
Efficient wheat lodging detection using UAV remote sensing images and an innovative multi-branch classification framework
10.3390/rs15184572 · 2023 · External reference
AAUConvNeXt: Enhancing crop lodging segmentation with optimized deep learning architectures
10.34133/plantphenomics.0182 · 2024 · External reference
Identifying rice lodging based on semantic segmentation architecture optimization with UAV remote sensing imaging
10.1016/j.compag.2024.109570 · 2024 · External reference
Unraveling the spatial-temporal patterns of typhoon impacts on maize during the milk stage in Northeast China in 2020
10.1016/j.eja.2024.127169 · 2024 · External reference
A review of the application of UAV multispectral remote sensing technology in precision agriculture
10.1007/978-981-96-5747-6 · 2025 · External reference
A multi-scale rice lodging monitoring method based on MSR-Lodfnet
10.3390/agriculture15232487 · 2025 · External reference
10.3390/rs12111838
10.3390/rs12111838 · External reference
Automatic wheat lodging detection and mapping in aerial imagery to support high-throughput phenotyping and in-season crop management
10.3390/agronomy10111762 · 2020 · External reference
Application of UAV RGB images and improved PSPNet network to the identification of wheat lodging areas
10.3390/agronomy13051309 · 2023 · External reference
UAV-multispectral based maize lodging stress assessment with machine and deep learning methods
10.3390/agriculture15010036 · 2024 · External reference
Evaluating maize emergence quality with multi-task YOLO11-Mamba and UAV-RGB remote sensing
2025 · External reference
A systematic review and assessment of inverse crop parameter modeling based on synthetic aperture radar data: research advances, existing problems, and future directions
10.1109/mgrs.2024.3454317 · 2025 · External reference
Use of unmanned aerial vehicle imagery and deep learning unet to extract rice lodging
10.3390/s19183859 · 2019 · External reference
Collaborative wheat lodging segmentation semi-supervised learning model based on RSE-BiSeNet using UAV imagery
10.3390/agronomy13112772 · 2023 · External reference
Remote sensing of regional-scale maize lodging using multitemporal GF-1 images
10.1117/1.jrs.14.014514 · 2020 · External reference
Analysis of plant height changes of lodged maize using UAV-LiDAR data
10.3390/agriculture10050146 · 2020 · External reference
Soybean yield estimation and lodging discrimination based on lightweight UAV and point cloud deep learning
10.1016/j.plaphe.2025.100028 · 2025 · External reference
Soybean yield estimation and lodging classification based on UAV multi-source data and self-supervised contrastive learning
10.1016/j.compag.2024.109822 · 2025 · External reference
WLUSNet: a lightweight wheat lodging segmentation network based on UAV image
10.1016/j.compag.2025.110587 · 2025 · External reference
Quantification of root lodging damage in corn using uncrewed aerial vehicle imagery
10.1002/cft2.20241 · ExternalCitation · doi-reference
A method for the assessment of the risk of wheat lodging
10.1006/jtbi.1998.0778 · ExternalCitation · doi-reference
A review of the application of UAV multispectral remote sensing technology in precision agriculture
10.1007/978-981-96-5747-6 · ExternalCitation · doi-reference
Highly efficient wheat lodging extraction algorithm based on two-peak search algorithm
10.1007/s11119-025-10223-7 · ExternalCitation · doi-reference
Damage assessment due to wheat lodging using UAV-based multispectral and thermal imageries
10.1007/s12524-023-01680-6 · ExternalCitation · doi-reference
Analysis of changes in rice yield components and vegetation indices in response to lodging timing during the grain-filling stage, lodging severity, and nitrogen fertilization
10.1007/s12892-025-00313-3 · ExternalCitation · doi-reference
Impact of climate change on agriculture production and its sustainable solutions
10.1007/s42398-019-00078-w · ExternalCitation · doi-reference
Estimates of rice lodging using indices derived from UAV visible and thermal infrared images
10.1016/j.agrformet.2018.01.021 · ExternalCitation · doi-reference
Spatial-temporal distribution and hazard assessment of maize lodging in a synergistic disaster environment
10.1016/j.agrformet.2023.109730 · ExternalCitation · doi-reference
Tracking the impact of typhoons on maize growth and recovery using Sentinel-1 and Sentinel-2 data: a case study of Northeast China
10.1016/j.agrformet.2024.110266 · ExternalCitation · doi-reference
A grid-level segmentation model based on encoder-decoder structure with multi-source features for crop lodging detection
10.1016/j.asoc.2023.111113 · ExternalCitation · doi-reference
Monitoring of maize lodging using multi-temporal Sentinel-1 SAR data
10.1016/j.asr.2019.09.034 · ExternalCitation · doi-reference
A compilation of UAV applications for precision agriculture
10.1016/j.comnet.2020.107148 · ExternalCitation · doi-reference
Deep learning in agriculture: a survey
10.1016/j.compag.2018.02.016 · ExternalCitation · doi-reference
UAV environmental perception and autonomous obstacle avoidance: a deep learning and depth camera combined solution
10.1016/j.compag.2020.105523 · ExternalCitation · doi-reference
Identifying sunflower lodging based on image fusion and deep semantic segmentation with UAV remote sensing imaging
10.1016/j.compag.2020.105812 · ExternalCitation · doi-reference
Adaptive autonomous UAV scouting for rice lodging assessment using edge computing with deep learning EDANet
10.1016/j.compag.2020.105817 · ExternalCitation · doi-reference
Automatic extraction of wheat lodging area based on transfer learning method and deeplabv3+ network
10.1016/j.compag.2020.105845 · ExternalCitation · doi-reference
Monitoring maize canopy chlorophyll density under lodging stress based on UAV hyperspectral imagery
10.1016/j.compag.2021.106671 · ExternalCitation · doi-reference
An explainable XGBoost model improved by SMOTE-ENN technique for maize lodging detection based on multi-source unmanned aerial vehicle images
10.1016/j.compag.2022.106804 · ExternalCitation · doi-reference
LodgeNet: improved rice lodging recognition using semantic segmentation of UAV high-resolution remote sensing images
10.1016/j.compag.2022.106873 · ExternalCitation · doi-reference
Drones in agriculture: a review and bibliometric analysis
10.1016/j.compag.2022.107017 · ExternalCitation · doi-reference
A new comprehensive index for monitoring maize lodging severity using UAV-based multi-spectral imagery
10.1016/j.compag.2022.107362 · ExternalCitation · doi-reference
LiDAR applications in precision agriculture for cultivating crops: a review of recent advances
10.1016/j.compag.2023.107737 · ExternalCitation · doi-reference
Comparison of the performance of multi-source three-dimensional structural data in the application of monitoring maize lodging
10.1016/j.compag.2023.107782 · ExternalCitation · doi-reference
RL-DeepLabv3+: a lightweight rice lodging semantic segmentation model for unmanned rice harvester
10.1016/j.compag.2023.107823 · ExternalCitation · doi-reference
Enhancing model performance in detecting lodging areas in wheat fields using UAV RGB Imagery: considering spatial and temporal variations
10.1016/j.compag.2023.108297 · ExternalCitation · doi-reference
Monitoring maize lodging severity based on multi-temporal Sentinel-1 images using Time-weighted Dynamic time Warping
10.1016/j.compag.2023.108365 · ExternalCitation · doi-reference
RTAL: an edge computing method for real-time rice lodging assessment
10.1016/j.compag.2023.108386 · ExternalCitation · doi-reference
Automatic detection of crop lodging from multitemporal satellite data based on the isolation forest algorithm
10.1016/j.compag.2023.108415 · ExternalCitation · doi-reference
A research review on deep learning combined with hyperspectral imaging in multiscale agricultural sensing
10.1016/j.compag.2023.108577 · ExternalCitation · doi-reference
Wind-induced response of rapeseed seedling stage and lodging prediction based on UAV imagery and machine learning methods
10.1016/j.compag.2024.108637 · ExternalCitation · doi-reference
Machine learning based plot level rice lodging assessment using multi-spectral UAV remote sensing
10.1016/j.compag.2024.108754 · ExternalCitation · doi-reference
Unmanned aerial vehicles (UAVs)-based crop lodging susceptibility and seed yield assessment during different growth stages of rapeseed (Brassica napus)
10.1016/j.compag.2024.108980 · ExternalCitation · doi-reference
Foundation models in smart agriculture: Basics, opportunities, and challenges
10.1016/j.compag.2024.109032 · ExternalCitation · doi-reference
A systematic review of hyperspectral imaging in precision agriculture: Analysis of its current state and future prospects
10.1016/j.compag.2024.109037 · ExternalCitation · doi-reference
Winter wheat weed detection based on deep learning models
10.1016/j.compag.2024.109448 · ExternalCitation · doi-reference
UAS-based remote sensing for agricultural monitoring: current status and perspectives
10.1016/j.compag.2024.109501 · ExternalCitation · doi-reference
Identifying rice lodging based on semantic segmentation architecture optimization with UAV remote sensing imaging
10.1016/j.compag.2024.109570 · ExternalCitation · doi-reference
Integrating UAV, UGV and UAV-UGV collaboration in future industrialized agriculture: Analysis, opportunities and challenges
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