PLANT-GPK v4.0: Multi-Stage Plant Phenotyping with Time-Discovery and Harvest Prediction
扩展PLANT-GPK框架，从单张图像反演植物生理参数与隐藏时间维度，实现跨生育期表型分析与收获期预
农业AI与大模型
人工智能算法、大模型与决策支持系统
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International Research Journal of Modernization in Engineering Technology and Science·10月17日 · 周六49 分 论文农业AI与大模型智慧农业 / 农业物联网阅读 1
AI SMART AGRO SYSTEM: A WEB-BASED AI-ASSISTED DECISION SUPPORT PLATFORM FOR FARMERS
构建一个面向农民的网页版AI决策支持平台，集成病害识别、选种、土壤、灌溉与天气建议。
A growing challenge: stakeholder perceptions of AI and ML applications in U.S. agriculture
通过问卷与访谈调查美国农业利益相关者对AI/ML应用的认知与障碍。
An entropy-guided dynamic lightweight network for identification of wild edible vegetables of BTR
提出熵引导动态轻量网络，用于识别BTR野生食用蔬菜。
A cross-domain review of artificial intelligence techniques for iot security, computer networks, image processing and smart agriculture in connected environments
综述AI在物联网安全、计算机网络、图像处理与智慧农业中的应用与局限。
Current applications of artificial intelligence for advancing agriculture, sustainability and climate mitigation
综述农业人工智能在精准灌溉、产量预测、病虫害监测等应用及落地挑战。
A Comprehensive Review on Multi-Modal Large Language Models and Agentic Architectures for Precision Agricultural Decision Support
综述多模态大模型与智能体架构在精准农业决策支持中的应用与不足。
A Comparative Study of Client-Level Stabilization Techniques in Federated Learning for Robust Plant Disease Recognition
比较联邦学习客户端级稳定化技术，提升植物病害识别的鲁棒性。
Lightweight Hybrid CNN-Transformer Network for Robust Maize Leaf Disease Detection and Edge Deployment
构建轻量MobileNetV3-Small框架实现玉米叶片病害分类并评估边缘部署。
Real-Time UAV scheduling under hazardous weather conditions using an integrated fuzzy logic and machine learning framework
提出融合模糊逻辑与机器学习分类器的无人机实时调度框架，在恶劣天气下保障精准农业飞行安全。
MSFANet: a multi-scale feature aggregation network for tobacco pest recognition
提出MSFANet多尺度特征聚合网络，实现复杂田间背景下烟草害虫的自动识别。
FDUNet-LRSA: efficient frequency-adaptive segmentation for automated crop disease inspection
提出频域自适应分割网络FDUNet-LRSA，用于甘薯病害自动巡检。
Predicting Wetland Nitrogen Levels Through Microbial Signatures: A Taxonomy-Based Approach Validated by Machine Learning
利用湿地微生物群落特征结合机器学习预测土壤总氮水平。
Artificial Intelligence for Environmental Sustainability and Climate Change Mitigation: Recent Advances, Challenges, and Future Perspectives
综述AI在气候变化缓解与环境可持续领域的应用进展、挑战与未来方向。
Explainable deep learning for Mango leaf disease recognition using AlexNet and grad-CAM
提出可解释深度学习框架，用AlexNet结合贝叶斯调参、微调和Grad-CAM实现芒果叶病十分类。
International Journal of Environmental and Agriculture Research·10月15日 · 周四62 分 论文农技推广与成果转化智慧农业 / 农业物联网阅读 0
The Importance of Electronic Communication in the Use of Artificial Intelligence Programs and Applications in the Field of Smart Agriculture from the Point of View of Agricultural Extension Workers in Nineveh Governorate, Iraq
调查伊拉克尼尼微省农业推广人员对电子通信在智慧农业AI应用中重要性的认知及障碍。
Trustworthy Explainable AI for Lettuce Growth Stage Prediction Using Sensor Data in Smart Agriculture
提出XGB-StageVision，用传感器数据与可解释AI预测水培生菜生长阶段。
An integrated instance segmentation and deep feature fusion model for robust leaf species classification in natural environments
提出实例分割与深度特征融合框架，在自然环境下实现鲁棒叶片物种分类。
Frontiers in Sustainable Food Systems 10 2026-10-15·10月15日 · 周四0 分 论文农业AI与大模型数字乡村与农业信息化2 个信源同时报道 阅读 1
Artificial intelligence policy, digital industry agglomeration, and industrial land intensive use: evidence from a quasi-natural experiment in China
以AI创新试验区为准自然实验，检验AI政策通过数字产业集聚促进工业用地集约利用。
Detection of yam leaf diseases and pest damage under complex field conditions using LIMN-YOLO
提出轻量级LIMN-YOLO模型，在复杂田间条件下检测山药叶部病害与虫害。