Rice Yield Prediction Using Multi-Modal Regression Learning with Optimized Ensemble Models
构建多模态回归学习框架，融合气候、遥感与作物因子，实现水稻产量连续预测。
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Assam 洪泛平原 水稻 遥感
同时包含 Assam、洪泛平原、水稻、遥感 的农业资讯，共 14 条。
Synergistic Use of Multitemporal SAR and Optical Data with Random Forest Approach for Rice Mapping in Bangladesh
融合Sentinel-1 SAR与Sentinel-2光学影像，用随机森林在GEE上绘制孟加拉国Bo
Integrating UAV-Based Remote Sensing and Deep Learning for Early Detection of Bacterial Leaf Blight in Rice
Integrating UAV-Based Remote Sensing and Deep Learning for Early Detection of Bacterial Leaf Blight in Rice。Research Square
Dual‐Branch Network With Enhanced Feature Fusion for Improved Rice Classification Accuracy
提出双分支深度学习网络融合时序与辅助数据，提升亚热带水稻分类精度。
Comprehensive remote sensing and machine learning framework for multi-regional rice yield forecasting under hydroclimatic variability in Sahelian Niger
结合遥感植被指数与机器学习，预测尼日尔萨赫勒四地区2010–2025年水稻产量。
Rice Cropping Pattern Mapping Using GEE-Based Sentinel-1/2 Time-Series Imagery and Machine Learning
基于GEE融合Sentinel-1/2时序与地形特征，用机器学习高精度制图长三角水稻种植模式。
Spatial and Temporal Analysis of Rice Yield Using the DSSAT Model in the Kommamuru Canal Command Area, Guntur (Dist), Andhra Pradesh, India
用DSSAT-CERES水稻模型结合Sentinel-2遥感，分析印度Guntur灌区2022-20
Spatiotemporal Deep Learning for Rice Plant Height Estimation from Multi-Temporal UAV RGB Imagery
提出Rice-STNet时空深度学习框架，用多时相无人机RGB影像估算水稻株高。
AgriMAC: An Attention Based Multimodal Deep Clustering Framework for Rice Health Assessment
提出无监督多模态聚类框架AgriMAC，融合无人机NDVI、IoT土壤与气象数据评估水稻健康。
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。
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
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。
Assessing rice genotype dependency in remote sensing: challenges in nitrogen discrimination and yield forecasting
评估遥感模型在不同水稻基因型间的可转移性，用于氮肥监测和产量预测。
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。