International Journal for Research in Applied Science and Engineering Technology·10月21日 · 周三65 分 论文遥感与农情监测数字乡村与农业信息化阅读 0
AI-Based RGB Imaging and 14-Channel Multispectral Food Quality Scanner
综述RGB与多光谱成像结合AI的食品品质无损检测，并提出一款集成14通道多光谱传感器的紧凑型扫描仪方
遥感与农情监测
卫星与无人机遥感、长势监测与产量估测
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Improving alfalfa nitrogen estimation with canopy structural priors from DSSAT–PROSAIL and UAV hyperspectral data
构建MALENet融合DSSAT-PROSAIL结构先验与无人机高光谱，提升苜蓿氮浓度估算精度。
Evaluation of Counterfactual Explanation Robustness for Computer Vision Agriculture Yield-Forecast Models Under Satellite Cloud-Mask Gaps: An Interpretability Reliability Bound for Cooperative Storage Decisions
推导卫星云掩膜缺口下反事实解释可靠性的理论界，并评估其对合作社储粮决策的影响。
INTEGRATING IoT, REMOTE SENSING, AND ARTIFICIAL INTELLIGENCE FOR SMART IRRIGATION: A REVIEW OF ARCHITECTURES, METHODS, AND CHALLENGES
综述物联网、遥感与人工智能融合的智能灌溉系统架构、方法与挑战。
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。
Mapping Soil Salinity in Arid Agricultural Regions Using Multi-Source Remote Sensing and a Long-Range Dependency-Enhanced Deep Learning Framework
提出LRD-Net深度学习框架，融合多源遥感与环境协变量，估算新疆干旱绿洲区土壤盐分。
Hierarchical cross-modal spatiotemporal attention network for crop yield prediction in complex Himalayan agroecosystems
提出分层跨模态时空注意力网络HCM-STAN，融合多源农业数据预测喜马拉雅山区苹果产量。
Wild boar collision data and satellite computer vision refine habitat suitability mapping across France
融合野猪碰撞数据与卫星视觉模型，预测法国野猪栖息地适宜性及其时空驱动因素。
Hybrid transformer and CNN for hyperspectral image classification with spectral band selection
提出结合波段选择与ViT-CNN混合框架的高光谱图像分类方法，提升小样本分类精度。
Wearable Sensors for Smart Agriculture: From Sensing Mechanisms to Crop Phenotyping and Harvesting Applications
综述柔性可穿戴传感器在智慧农业中的传感机制、作物表型监测与采收应用。
Early Detection of Apple Scab in Orchards and Mildew in Vineyards Using A Novel Deep Learning Model and Multispectral Imagery
提出一种基于无人机多光谱时序影像的深度学习混合模型，实现苹果黑星病和葡萄霉病的早期检测与分割。
Applications of Neutrosophic Topology in the Indian Context: A Review and Emerging Research Directions
综述中智拓扑在印度多领域的应用潜力，并指出理论与实证数据脱节的局限。
Reducing redundancy in multi-temporal analysis to improve field-scale detection of crop residue burning
用多时相遥感与模糊机器学习减少重复检测，提升稻田秸秆焚烧田块尺度制图精度。
Seeing Crops in 3D: Remote Sensing for Smarter Precision Farming
提出融合物联网、厘米级GNSS、多光谱遥感和AI的精准农业框架，构建作物数字孪生。
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。
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
A SwiGLU enhanced ConvNeXt framework for multispectral Sentinel-2 land use and land cover classification
提出SwiGLU增强的ConvNeXt框架，融合多光谱波段与指数集成分类Sentinel-2土地利用
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。
HyBEAR: a hyperspectral benchmark for bare soil detection
提出HyBEAR高光谱航空影像基准数据集，用于整田块裸土检测。
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。