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。
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农业人工智能 计算机视觉
同时包含 农业人工智能、计算机视觉 的农业资讯，共 39 条。
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。
YOLO-Based Real-Time Object Detection Using Computer Vision for Robotics
提出将轻量YOLO检测器与机器人相机集成的框架，并定义原型评估方案。
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。
International Journal of Scientific Research in Computer Science Engineering and Information Technology·10月18日 · 周日0 分 论文智慧农业 / 农业物联网阅读 0
Food Recognition and Nutrition Estimator Using Computer Vision and Machine Learning
开发CrunchUP网页应用，拍照识别食物并估算营养，结合个人目标给出膳食建议。
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。
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。
Biology-aware association for identity-consistent leaf tracking in top-down plant phenotyping
提出融合外观与三种生物几何线索的关联模块，实现叶片身份一致跟踪。
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。
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。
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。
Addressing scale Variation and texture confusion in strawberry phenology detection via a lightweight synergistic network
提出轻量协同网络，解决草莓物候检测中的尺度变化与纹理混淆问题。
Geometric representation-based facial keypoint matching for sheep identification across growth stages
提出基于面部关键点几何表示的绵羊识别方法，可跨生长阶段匹配。
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%。
Accelerated development and deployment of computer vision models for invasive aquatic pests
提出一套开发与部署水生入侵物种计算机视觉模型的实用框架，并在新西兰三种入侵物种上验证。
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。
Brazilian Insect Survey: A Platform for Pest Management
巴西昆虫调查平台整合计算机视觉、田间试验与种群建模，实现害虫实时监测与治理。
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering·9月18日 · 周五0 分 论文智慧农业 / 农业物联网阅读 1
Computer vision and artificial intelligence system for real-time detection of the use of personal protective equipment in industrial environments
提出基于YOLOv8和树莓派的实时个人防护装备检测系统，准确率96.5%。
AshGdNutDefAM: Machine-learning-based multi-feature framework for nutrient deficiency detection and classification in Ash gourd Plant
提出AshGdNutDefAM多特征机器学习框架，自动检测和分类冬瓜缺镁缺铁症状。
Multi-Species Egg Morphometry and Weight Prediction Using Computer Vision
Multi-Species Egg Morphometry and Weight Prediction Using Computer Vision。Research Square
International Journal of Electrical and Electronics Engineering·9月14日 · 周一77 分 论文农业AI与大模型智慧农业 / 农业物联网阅读 2
Automated Cocoa Bean Classification and Defect Detection Based on ASEAN Standard Using Image Processing and Feature-Based Analysis
基于图像处理与特征分析，按东盟标准自动分类可可豆并检测缺陷。
Evaluation of hybrid models based on image segmentation and inference for pig weight estimation
用YOLOv8n-seg分割猪体并提取EfficientNet特征，结合回归模型实现非侵入式猪体重估
ABUAD Journal of Engineering Research and Development (AJERD)·9月12日 · 周六71 分 论文农业AI与大模型农业人工智能与决策模型阅读 2
Quality Assessment of Scotch Bonnet Pepper (Capsicum Chinense Jacq) Using Image Processing Techniques
用图像处理和CNN/SVM/逻辑回归对苏格兰帽椒进行好坏二分类质量分级。
Spectral Transforms as a Tool to Optimize Digital Phenotyping in Biological Images
用离散小波变换提取蛋壳图像多尺度空间特征，实现小样本高效数字表型。
Wild rice kernel inspection using a prompt-guided vision language model with evidence-grounded reasoning
用提示引导的视觉语言模型对野生稻米粒进行检测，并给出基于证据的推理。
Two Decades of Computer Vision in Precision Livestock Farming: an Umbrella Review of Applications, Benchmarking Evidence, and the Performance-to-Deployment Gap Across Cattle, Pig, and Poultry Systems
伞式综述112篇综述，梳理牛猪禽精准养殖计算机视觉应用与部署差距。
Identifying mounting behaviour in boars using deep learning-based instance segmentation and binary classification - a pilot study
提出基于Mask R-CNN和SVM的猪爬跨行为自动检测方法，实现群养公猪连续监测。
Video-based fruit detection and tracking: effects of scanning conditions on fruit load estimation
研究视频多目标跟踪系统在不同扫描条件下估算苹果产量的性能。
Monitorización continua y autónoma de árboles frutales mediante imagen
用固定可见光传感器和AI视觉技术，连续监测柑橘果实生长与成熟。