Capturing Spatial Heterogeneity Using UAV-Derived Multispectral Phenotypes and Random Regression Models Improves Genetic Evaluation in Alfalfa Breeding Trials
用无人机多光谱时序表型和随机回归模型校正田间空间异质性，提升苜蓿育种遗传评估精度。
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斑点矢车菊 无人机 遥感
同时包含 斑点矢车菊、无人机、遥感 的农业资讯，共 26 条。
Barley head detection using UAV imagery and YOLOv10
Barley head detection using UAV imagery and YOLOv10。Precision Agriculture
UAV-based estimation of aboveground biomass carbon in the Sundarbans mangrove forest of Bangladesh
利用无人机冠层指标与地面数据估算孟加拉孙德尔本斯红树林地上生物量碳。
Application of Deep Learning Techniques for Vineyard Mapping and Characterization Using Multispectral UAV Imagery: A Case Study from Northern Greece
用多光谱无人机影像和深度学习实现葡萄园制图与冠层特征提取。
Road surface material classification from unmanned aerial vehicle red, green, blue and multispectral imagery using spectral features and ensemble machine learning model
用无人机RGB与多光谱影像结合集成机器学习，分类路面材料并验证多光谱与纹理特征的增益。
The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy·10月2日 · 周五0 分 论文智慧农业 / 农业物联网阅读 0
Системи на основі YOLO для виявлення вибухонебезпечних залишків війни: огляд для гуманітарного розмінування
综述YOLO模型在无人机人道排雷中检测战争爆炸残留物的应用与局限。
YOLO-BASED SYSTEMS FOR DETECTING EXPLOSIVE REMNANTS OF WAR: A REVIEW FOR HUMANITARIAN DEMINING
综述YOLO模型在无人机人道排雷中检测地雷与未爆弹药的技术管线。
Direct surface reflectance retrieval from UAV multispectral imagery using onboard upward-looking spectrometer with MLR under variable illuminations
利用无人机搭载向上光谱仪与多元线性回归，从多光谱影像直接反演地表反射率。
ANÁLISE COMPARATIVA DE SENSORES RGB E LiDAR APLICADOS À TOPOGRAFIA COM DRONES EM ÁREAS AGRÍCOLAS
对比无人机RGB与LiDAR传感器在甘蔗田地形测绘中的精度与适用性。
Multisensor data fusion from uav platforms: a robust approach for estimating photosynthetic capacity across vertical leaf layers in winter wheat
Multisensor data fusion from uav platforms: a robust approach for estimating photosynthetic capacity across vertical leaf layers in winter wheat。Precision Agriculture
Comparison of NDVI obtained from an active proximal sensor and UAV multispectral imagery in coffee
Comparison of NDVI obtained from an active proximal sensor and UAV multispectral imagery in coffee。Research Square
Adversarial Patch and Camouflage Attacks on Aerial Object Detection: A Geometry-Aware Review
综述无人机与遥感目标检测中的对抗补丁与伪装攻击及防御，并提出几何感知分类体系。
Optimizing canopy nitrogen retrieval in wheat from high-resolution UAV hyperspectral data using RTM-based Gaussian process regression
用PROSAIL-PRO与高斯过程回归从无人机高光谱数据反演小麦冠层氮含量。
UAV photogrammetry and remote sensing for coastal biodiversity and habitat conservation
综述无人机摄影测量与遥感在海岸生物多样性和栖息地保护中的应用与局限。
UAV无人机高光谱图像土壤盐度制图(湿度校正)——MDPI Agronomy
用无人机高光谱结合Stacking集成模型实现湿度干扰下的土壤盐度制图。
Estimation of crop canopy nitrogen content using deep transfer learning with PROSAIL-PRO model and UAV hyperspectral imagery
融合PROSAIL-PRO物理模型与深度迁移学习，用无人机高光谱估算作物冠层氮含量。
Genotype-Aware Prediction of Soybean Seed Composition from Multimodal UAV Imagery of the Standing Crop
用无人机多模态影像与基因型数据训练CNN，预测大豆八种种子成分。
Estimation of field-scale crop evapotranspiration from the mechanistic SIF-ET model using the UAV hyperspectral imagery
利用无人机高光谱影像构建田间尺度SIF-ET机理模型，实现作物蒸散发高精度估算。
Lightweight nighttime citrus fruit detection in UAV imagery using an enhanced NightNet
提出增强NightNet实现无人机夜间柑橘果实轻量检测。
A source-side trait-mediated framework for dynamic maize yield prediction using UAV multispectral imagery
提出基于无人机多光谱的源端性状中介框架，实现玉米动态产量预测。
“Space-sky-ground-Lake” four-dimensional monitoring technology for water quality in Baiyangdian - a new model for future environmental monitoring
构建“天-空-地-湖”四维水质监测系统，实现白洋淀水质立体化智能监控。
Adaptive feature learning and wavelet preservation for forest canopy mapping from UAV imagery
提出自适应特征学习与小波保持方法，用于无人机影像的森林冠层制图。
Lightweight Near-Infrared Spectral Reconstruction from Red UAV Imagery Using Artificial Intelligence for Low-Cost Remote Sensing
用仅含609个参数的MLP从UAV红光波段重建近红外波段，低成本替代多光谱相机。
AI Drones Unlock Hidden Avocado & Hazelnut Secrets（Information Processing in Agriculture）
开发基于AI的无人机系统，用无监督算法从航拍图像估算果树高度和冠层体积。
基于无人机多源遥感特征的茶树生长与氮素状况深度学习监测
融合无人机多源遥感特征与深度学习，高精度估算茶树生物量与氮素积累量。
Tea Shoot Category Detection Based on UAV Remote Sensing(MDPI Agronomy 2026-08-17)
基于无人机遥感的茶梢类别检测。研究利用UAV遥感图像对茶树新梢进行自动分类检测,支持茶园精细化管理与产量预测。通过深度学习方法识别不同生长阶段的茶梢,助力茶叶采摘决策与品质分级,为茶产业数字化转型提供技术支撑。