Modeling runoff, sediment, and nutrient dynamics in the Ganjiang River Basin, China: A hierarchical SWAT-BiLSTM framework
提出SWAT-BiLSTM分层混合框架，高精度模拟赣江流域径流、泥沙与营养物动态。
农业AI与大模型
人工智能算法、大模型与决策支持系统
技术筛选
642 篇内容
Water Optimizer: A Tool for Decision Support and Policy Analysis
开发了Water Optimizer工具，在有限供水下优化作物种植与灌溉量以最大化利润。
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND MATHEMATICAL THEORY E-ISSN·10月12日 · 周一75 分 论文农业AI与大模型农业人工智能与决策模型阅读 2
Deep Learning Approaches for Plant Disease Detection: A Review of Convolutional Neural Networks and Emerging Techniques
综述深度学习在植物病害检测中的应用，涵盖CNN、混合Transformer、注意力机制与生成式数据增
Role of Artificial Intelligence in Advancing Biotechnology: A Comprehensive Review
综述人工智能在生物技术各领域的应用现状、工具、挑战与未来方向。
Ontologies in Precision Agriculture—A brief Survey on Reproducibility
综述85篇精准农业本体论文，发现数据、本体和代码可复现率极低。
PEAS-DeiT: Multi-Scale Spatial Attention Enhanced DeiT for Pea Leaf Disease Classification
提出PEAS-DeiT模型，将多尺度空间注意力融入DeiT，实现豌豆叶片病害分类。
Integrating earth observation and machine learning for forest fire risk assessment in Rasuwa district, Nepal
整合地球观测与随机森林模型评估尼泊尔Rasuwa地区森林火灾风险。
An Interpretable Deep Learning Framework for Spatial Prediction of Soil Salinity Using Multi-Source Remote Sensing and Environmental Data: A Case Study of Cangzhou, Hebei Province, China
构建融合多源遥感与环境变量的可解释深度学习框架，预测沧州土壤盐分空间分布。
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。
GREEN TECH PARADOX An Analysis of AI in Environment Sustainability
批判分析AI在环境可持续中的双重角色，揭示其生态收益可能被硬件生命周期成本抵消。
YOLO-Based Leaf Disease Detection in Smart Agriculture: Evolution, Task Adaptation, and Deployment Challenges
综述了基于YOLO的叶片病害检测的演进、任务适配与部署挑战。
Climate policy uncertainty and domestic–international grain-market risk spillovers: a TVP-VAR-BK analysis with machine learning early warning
用TVP-VAR-BK与机器学习分析气候政策不确定性对中外粮食市场风险溢出的动态影响。
From Handcrafted Descriptors to Deep Embeddings: A Comparative Study for Regional Hazelnut Image Classification
比较手工特征、深度迁移学习和量子兼容分类器对三个地区榛子图像的分类性能。
Hybrid Deep Feature Extraction and Ensemble Machine Learning for Potato Leaf Disease Classification in Uncontrolled Field Conditions
融合三种CNN深度特征与集成学习，实现田间马铃薯叶片七类病害分类。
Explainable deep learning framework for real-time insect pest detection in smart agriculture
提出可解释深度学习框架CPSA-RIPD-CSTGCN，实现智慧农业中害虫实时检测。
Enhanced crop yield estimation in smart agriculture via AI and IoT using the GODL geo-optimized algorithm
提出GODL算法，融合地理空间信息与深度学习，结合AI和IoT提升作物产量预测精度。
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。
A study on the identification of wheat powdery mildew using chlorophyll fluorescence imaging
该研究利用叶绿素荧光成像与深度学习识别小麦白粉病并分级。
Comparative Deep Learning and RISE-Based Explainable AI Framework for Orange Fruit Disease Detection
比较三种深度学习模型检测橙子病害，并用RISE提升可解释性。
A Privacy-Preserving Federated Learning Framework for Paddy Leaf Disease Detection Using an Enhanced Pretrained Novel EfficientNet-Lite4 Model
提出联邦学习结合改进EfficientNet-Lite4的水稻叶片病害检测框架，兼顾隐私与精度。