Calibration-Shift Inference for Computer Vision Agriculture Yield Models Under Retrofit Sensor Replacement: An Artificial Intelligence Post-Deployment Recalibration Guarantee
提出改造传感器替换后视觉产量模型校准漂移的检测与置信区间保证方法。
数字农业与前沿技术
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Distributionally-Robust Evaluation of Computer Vision Agriculture Disease Classifiers Under Climate-Driven Pathogen Range Shifts: An Artificial Intelligence Worst-Case Generalization Bound
提出气候校准的分布鲁棒评估准则，替代i.i.d.假设评价作物病害视觉分类器。
A Comprehensive Review of Deep Learning and Computer Vision Techniques for Fruit Quality Assessment and Classification
系统综述深度学习与计算机视觉在水果品质评估与分级中的全流程方法。
牛肉牛区域特征计算机视觉分析:基于 YOLO 与深度估计的牛体况自动评分
用YOLO检测与深度估计提取牛体区域特征，实现肉牛体况自动评分。
Enhancing seeding efficiency using a computer vision system to monitor furrow quality in real-time
Enhancing seeding efficiency using a computer vision system to monitor furrow quality in real-time。Precision Agriculture
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。
Deep learning-based estimation of Kent mango yield by commercial export category under real field conditions in northern Peru
开发深度学习模型在真实田间条件下检测并分类肯特芒果为三个出口等级，实现产量估计。
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。
An empirical performance comparison of deep learning models for apple leaf disease recognition
用UNet++分割苹果病叶并融合多种CNN与ViT分类，实现98.85%识别准确率。
Deep learning–based computer vision for rapid and accurate quantitative field assessment of powdery mildew severity: model comparison, validation, and agreement with human raters
开发并验证基于深度学习的计算机视觉流程，用手机图像快速定量评估豌豆白粉病严重度。
SMART GREENHOUSE MEASUREMENT AND MONITORING SYSTEM BASED ON IOT AND COMPUTER VISION
集成物联网与计算机视觉的智能温室系统，实现非破坏性植物生长监测与远程管控。
Knowledge Distillation for Hybrid CNN–Vision Transformer Architectures: A Systematic Review
系统综述2015-2026年混合CNN-ViT架构的知识蒸馏方法，按迁移方向、知识类型和应用领域分类
Animal welfare in the world of digitalization: Computer Vision in the context of foundational structures
论文论证计算机视觉用于动物福利时，伦理问题须置于社会基础结构中理解。
Zenodo (CERN European Organization for Nuclear Research)·10月5日 · 周一60 分 论文农业AI与大模型智慧农业 / 农业物联网2 个信源同时报道 阅读 2
Deep Learning for Early Disease Identification in Leaves: A Pathway to Sustainable Mango Production
综述深度学习与计算机视觉在芒果叶片病害早期识别中的应用，梳理三代技术并展望可持续种植。
Automated dairy cattle lameness assessment using a 38-keypoint whole-body YOLOv8 pose framework
构建38关键点全身YOLOv8姿态框架，实现奶牛跛行自动评估并与Sprecher评分比对。
Zenodo (CERN European Organization for Nuclear Research)·10月3日 · 周六58 分 论文农业AI与大模型农业遥感与作物表型2 个信源同时报道 阅读 4
A Comprehensive Review Of Image Processing Techniques: Classical Methods, Deep Learning, Applications, And Recent Advances
综述图像处理从经典方法到深度学习的技术演进、应用与挑战。
WeedNet: a foundation model-based global-to-local AI approach for weed species identification and classification
提出WeedNet基础模型，实现全球杂草物种识别与区域微调。
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。
Designing a framework for Sustainable Smart Agriculture with Mobile Robots and CNN
提出移动机器人结合CNN识别花卉的智能园艺框架，测试准确率达95%。
RootQuantV2: Adapting a Vision Foundation Model for Root-Trait Regression from Minirhizotron Imagery
用冻结DINOv3 ViT微调回归，从微根管图像直接预测根系长度和面积。