Evaluating Mesh Reconstruction Methods for Crop Phenotyping
评估7种网格重建流程在作物表型三维数字化中的保真度与一致性。
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农业人工智能 智慧农业 遥感
同时包含 农业人工智能、智慧农业、遥感 的农业资讯，共 53 条。
Automated Machine Learning-Driven UAV Remote Sensing for Accurate Winter Wheat Water Content Prediction
用无人机多光谱、RGB和热红外遥感结合AutoML预测冬小麦含水量。
Red-Edge Information in Agricultural Remote Sensing: From Spectral Theory to Explainable Machine Learning
综述红边遥感在农业中的物理基础、条件依赖性与可解释机器学习中的新角色。
Application of Remote Sensing and Machine Learning in Sustainable Agriculture
综述遥感与机器学习在可持续农业中的应用现状与前景。
Deep learning-based classification of wet direct seeded rice, broadcasted direct seeded rice and transplanted rice using drone imagery for precision agriculture
用无人机可见光影像和深度学习模型区分直播稻、湿直播稻与移栽稻三种水稻种植方式。
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。
Transformer-Fused Hybrid Descriptors for Remote Sensing Scene Classification, Integrating Texture-Morphology Features with EfficientNetV2 Semantic Embeddings on MLRSNet
提出Transformer融合手工纹理形态特征与EfficientNetV2深度特征的遥感场景分类模
Empowering India's Digital Future through Artificial Intelligence in Geography
本文探讨地理空间人工智能（GeoAI）如何推动印度数字治理与可持续发展。
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。
Zenodo (CERN European Organization for Nuclear Research)·9月30日 · 周三46 分 论文智慧农业 / 农业物联网2 个信源同时报道 阅读 0
Uses of Artificial Intelligence In Geography
综述人工智能在地理学中的应用，涵盖GIS、遥感、城市规划、农业与环境监测等。
UAV-based rice nitrogen status monitoring using machine learning and deep learning
UAV-based rice nitrogen status monitoring using machine learning and deep learning。Precision Agriculture
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。
Predicting plant leaf functional traits using 2D spectral representation and multi-task learning with multi-gate mixture-of-experts
用二维光谱表示与多门混合专家多任务学习预测植物叶片功能性状。
《基于遥感的农作物产量估算综述:机器学习技术及环境、算法和硬件限制》
系统综述遥感估产方法，分类传感器、平台、建模与机器学习，指出深度学习性能最优。
A Robust and Efficient Scheme for Real-Time SAR Speckle Noise Reduction based on Attentional Self-Supervised Contrastive Deep Learning
提出RAST-Net，用注意力自监督对比深度学习实现SAR图像实时去斑。
Crop Simulation Model: A Digital Tool for Sustainable Water Management in Agriculture
综述作物模拟模型在估算作物需水与灌溉管理中的应用及改进方向。
Multi-grained image-text retrieval in farmland remote sensing via multimodal large language models
提出农田遥感图文跨模态检索任务，构建数据集并提出FarmMGR框架实现语言驱动检索。
A Hybrid Transfer Learning Framework for Seasonal Classification of Satellite Images
提出混合迁移学习框架，用预训练模型提取特征并结合机器学习分类器实现卫星图像季节分类。
An Optimized Temporal Attention-based Deep Learning Framwork for Accurate Crop Yield Prediction from Multi-source Agricultural Data
提出TA-ABC-Bi-LSTM模型，用多源农业数据精准预测水稻产量。
Machine Learning-Based Prediction of Fall Armyworm (Spodoptera frugiperda) Outbreaks in Maize Production Systems of Northern Nigeria Using Climate and Remote Sensing Data
用气候与遥感数据构建机器学习模型预测尼日利亚北部玉米草地贪夜蛾暴发。
Quantifying Thermoregulation in Niche Construction of Apis mellifera as an Extended Phenotype to Map the Selection Pressure of Volatile Climate Using Hybrid CNN Bi-LSTM Architecture and Remote Sensing
Quantifying Thermoregulation in Niche Construction of Apis mellifera as an Extended Phenotype to Map the Selection Pressure of Volatile Climate Using Hybrid CNN Bi-LSTM Architecture and Remote Sensing。Research Square
AgroInsect: A hybrid AI-driven edge-cloud architecture for precision pest detection and geostatistical interpolation in agriculture
提出AgroInsect边缘-云混合AI架构，实现农田害虫精准检测与地统计插值。
Transfer learning integrated with SCOPE model for maize yield prediction based on spectral data for different spatial scales
结合迁移学习与SCOPE模型，利用不同空间尺度光谱数据预测玉米产量。
Accelerated Computation of Vegetation Indices on Heterogeneous Platforms Using OpenMP, CUDA, and OpenCL for Sustainable Agricultural Monitoring
评估异构平台加速NDVI和NDWI计算，实现可持续农业监测。
An Interpretable BO-TCBDA Deep Learning Framework for Winter Wheat Yield Estimation Using Multi-Source Remote Sensing Data
提出BO-TCBDA深度学习框架，融合多源遥感数据估算冬小麦产量，兼具高精度与可解释性。
农业大模型在田间地头的落地实践：伏羲大脑"佳家农"智慧农服平台案例研究
介绍伏羲大脑农业大模型在佳木斯农高区的落地实践，通过手机和卫星数据提供农事指导，服务超5.6万农户。
Continuous monitoring of deficit irrigation in avocado across two contrasting rainfall years using sensor networks, telemetry, and machine learning
通过传感器、遥感和机器学习连续监测两年不同降雨下鳄梨的亏缺灌溉响应。
活力中国调研行｜农户有了数字新农具——黑龙江佳木斯佳家农智慧农服平台服务超6万户
新华社记者随活力中国调研行采访团走进黑龙江佳木斯国家农业高新技术产业示范区，佳家农智慧农服平台由佳木斯国家农高区联合中国科学院计算技术研究所打造，依托伏羲大脑农业大模型汇集卫星遥感、气象、土壤、作物长势、病虫害等多源数据；目前已服务农户超过6万户、覆盖耕地超过700万亩。
SMFS-RF: a knowledge-guided machine-learning method for crop phenology extraction from fine-resolution vegetation index data
SMFS-RF: a knowledge-guided machine-learning method for crop phenology extraction from fine-resolution vegetation index data。Remote Sensing of Environment
Integrating Geospatial Information and Artificial Intelligence for Irrigation Planning in Kwali Area Council, Federal Capital Territory, Nigeria
结合地理空间与AI评估尼日利亚Wako灌区适宜性，划分灌溉分区。
CAFF-Net for coupled eco-health prediction of urban green space and water body with multi-source remote sensing
提出CAFF-Net，用多源遥感数据耦合预测城市绿地和水体生态健康。
VGG21 Deep Learning + Drone Multispectral Imagery Detects Wheat Waterlogging Stress and Silicon Fertilizer Effects
用无人机多光谱和VGG21深度学习检测小麦涝害并评估硅肥效果。
Advanced Remote Sensing and AI Techniques in Agriculture and Forestry
综述遥感和AI在农林领域的先进技术及其应用。
Super-Resolution-Assisted Farmland Boundary Extraction from Medium-Resolution Satellite Image: A Real-ESRGAN and YOLO Segmentation Framework
提出结合Real-ESRGAN超分辨率和YOLO分割的农田边界提取框架，提升中分辨率卫星影像识别精度
International Research Journal of Modernization in Engineering Technology and Science·9月3日 · 周四73 分 论文智慧农业 / 农业物联网阅读 0
AGRITWIN AI: A DIGITAL TWIN AND MULTIMODAL EXPLAINABLE AI FRAMEWORK FOR PRECISION AGRICULTURE USING SATELLITE IMAGERY, IOT SENSORS, WEATHER INTELLIGENCE, LARGE LANGUAGE MODELS, AND RETRIEVAL-AUGMENTED GENERATION
提出 AgriTwin AI 框架，融合数字孪生与多模态可解释 AI，弥合农业数据与认知鸿沟。
Continual Learning Model Evaluation for Hyperspectral-Based Tomato Bacterial Spot Detection in Greenhouse
评估持续学习框架用于温室高光谱番茄细菌性斑点病冠层检测。
A physics-guided hybrid framework for peanut nitrogen monitoring (Computers and Electronics in Agriculture)
提出物理-数据融合框架POSNH，用于花生冠层氮素含量遥感监测，降低样本依赖并提高泛化能力。
Deep Learning Based Semantic Segmentation of Satellite Imagery for Land Cover Classification
综述深度学习用于卫星影像土地覆盖分类的语义分割方法，并分析挑战与未来方向。
MetaMamba: Meta-learning with mamba for few-shot vegetation species classification using UAV-based hyperspectral imagery in desert rangeland
提出MetaMamba方法，结合元学习与Mamba，实现荒漠草原无人机高光谱影像少样本植被物种分类。
An Improved Transformer-KAN Model for Soybean Mapping Based on Multi-Temporal Remote Sensing Data
提出改进的Transformer-KAN模型，基于多时相遥感数据实现高精度、可迁移的大豆种植区制图。
A dictionary-based method for crop yield prediction using satellite remote sensing data
提出基于HYDRA字典方法的机器学习框架，结合物候特征预测玉米产量。
Hyperspectral Imaging for Disease Detection in Wheat Crops: A Comprehensive Survey
综述高光谱成像在小麦病害检测中的应用，涵盖方法、挑战与未来方向。
CFAEVM-UNet: cross-fusion attention enhanced VM-UNet for UAV image segmentation of small and dense field crop pests
提出CFAEVM-UNet模型，用于无人机图像中密集小害虫的精确分割。
Diag-STFN：用于全球收获前作物产量预测的诊断时空多模态融合网络
提出Diag-STFN网络，用于全球收获前玉米和小麦产量预测，在CY-Bench基准上取得最优性能。
International Journal of Engineering Technology Research & Management·12月21日 · 周一30 分 论文农业人工智能与决策模型2 个信源同时报道 阅读 0
PRECISION AGRICULTURE ANALYTICS USING UAV MULTISPECTRAL IMAGING AND MACHINE LEARNING FOR CROP STRESS DETECTION AND YIELD OPTIMIZATION MODELS
利用无人机多光谱成像与机器学习检测作物胁迫并优化产量。
PhenoStream: A Cyberinfrastructure for Automated and AI-Based Crop Trait Extraction from Aerial Imagery
提出 PhenoStream 网络基础设施，自动化航空影像作物性状提取全流程。
MDFNet: a lightweight multi-stream network tailored for real-time GIS and disaster monitoring applications
提出轻量级多流双阶段融合网络MDFNet，用于高分辨率遥感图像场景分类，兼顾精度与效率。
Remote Sensing and Machine Learning for Futuristic Horticulture: A Comprehensive Review
综述遥感与机器学习在印度园艺作物精准管理中的应用，涵盖原理、方法、案例与挑战。
Integrating UAV-derived enhanced disease detection index and texture features for monitoring southern corn rust severity
结合无人机增强病害检测指数与纹理特征，监测南方玉米锈病严重度。
Combining 3D-multispectral and hyperspectral imaging to identify environmental stress treatments imposed during plant growth
结合3D多光谱和2D高光谱成像及机器学习，识别植物生长期间的环境胁迫处理。
Restoration of occlusion in residual film images and curling degree prediction based on UAV in pre-sowing cotton fields
用无人机图像修复残膜遮挡并预测卷曲程度，评估棉田残膜污染。
Transfer learning and multi-branch intermediate fusion deep neural network for wheat nitrogen concentration monitoring using multi-scale multi-modal remote sensing information
提出迁移学习与多分支中间融合深度网络，利用多尺度多模态遥感监测小麦氮浓度。
Rice seedling diagnosis of light and water stress based on green – blue channel feature enhancement
提出基于绿蓝通道特征增强的水稻幼苗光水胁迫诊断方法。