IoT-Based Automatic Cotton Leaf Disease Detection, Infection Percentage Estimation, and Treatment Recommendation Using Raspberry PI
基于树莓派与物联网，实现棉花叶病自动检测、感染率估算与防治推荐。
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多尺度异构特征协同的棉花叶片病害检测模型(Multi-Scale Heterogeneous Synergistic Model for Cotton Leaf Disease Detection)
提出MHSF-DETR棉花叶片病害检测模型，提升精度并降低参数量与计算量。
Optimization model of agricultural economic structure based on LSTM
用LSTM预测湖北农业经济指标，并构建多目标优化模型调整农业结构。
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 multimodal deep learning for rice crop health monitoring using vegetation index feature selection
融合Sentinel-1/2植被指数与气象数据，用多模态深度学习监测水稻健康。
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。
Severity Grading of Early Visible Symptoms of Sugarcane Pokkah Boeng Disease Based on Multi-Scale Dynamic Feature Fusion and Channel-Spatial Interaction: An On-Device Framework
提出轻量级框架，对甘蔗凤梨病早期可见症状进行四级严重度分级。
UGV based multi-RGBD SLAM framework for high-throughput in-situ 3D phenotyping of field maize
提出UGV搭载多RGBD相机的田间玉米原位3D表型系统，实现高通量三维重建与性状提取。
YOLOv8-MST: a lightweight and efficient real-time detection and counting deep learning algorithm for double-grain peanut seeding
提出YOLOv8-MST轻量算法，实现双粒花生播种实时检测与计数。
A physical-context-conditioned multimodal fusion network for estimating maize canopy nitrogen content using multi-source UAV remote sensing data
提出物理上下文条件化多模态融合网络，用多源无人机遥感估算玉米冠层氮含量。
A gradient-enhanced lightweight network for peanut leaf disease segmentation in complex field scenarios
提出梯度增强轻量网络，用于复杂田间场景下花生叶部病害分割。
International Journal of Business Arts and Scientific Study·9月30日 · 周三63 分 论文肥料与水肥一体化农业人工智能与决策模型阅读 2
Automated Leaf Color Chart (LCC)-BasedNitrogen Fertilizer Recommendation UsingPaddy Leaf Image Color Classification
用深度学习对水稻叶片颜色分级，并结合多模态大模型实时推荐氮肥用量。
UAV-based RGB imagery and supervised–unsupervised machine learning for estimating sorghum biomass and grain yield under water and nitrogen stress
用无人机RGB影像与机器学习估算水分氮胁迫下高粱生物量和产量。
Zenodo (CERN European Organization for Nuclear Research)·9月30日 · 周三75 分 论文薯类与杂粮农业人工智能与决策模型2 个信源同时报道 阅读 3
Lightweight Edge-AI Model for Real-Time Sorghum Disease Detection on Resource-Constrained Mobile Devices
开发轻量级边缘AI模型，在资源受限移动设备上实时检测高粱病害。
International Journal of Emerging Technologies and Innovative Research·9月30日 · 周三56 分 论文薯类与杂粮农业人工智能与决策模型4 个信源同时报道 阅读 3
An Integrated Computer Vision and Machine Learning Framework for Sorghum Disease Severity Assessment and Yield Prediction
融合计算机视觉与机器学习，实现高粱病害严重度评估与产量预测。
Raspberry Pi Lightweight Deep Learning Models Deployed for Corn Growth Stage Classification Using PhenoCam Images
用PhenoCam图像训练轻量深度学习模型，在树莓派上实时分类玉米8个生长阶段。
Hybrid Rule-Based and Machine Learning Decision-Support Framework for Smart Paddy Farming
提出规则与机器学习混合的水稻决策支持框架，提升决策精度并节水增产。
Reliability Auditing and Capacity-Constrained Review for Wheat-Yield Decision Support under Temporal and Spatial Shift
Reliability Auditing and Capacity-Constrained Review for Wheat-Yield Decision Support under Temporal and Spatial Shift。Research Square
AI-Assisted Demand Forecasting and Production Scheduling for High-Volume Food Manufacturing in Saudi Arabia: A Food Security Framework for Vision 2030
综述2020-2025年AI需求预测与生产调度研究，提出沙特食品制造整合框架以保障Vision 20