Detection of Potato Plant Leaf Diseases using Convolutional Neural Networks
提出轻量CNN实现马铃薯早疫病与晚疫病三分类，并在埃塞俄比亚田间验证。
薯类与杂粮
马铃薯、甘薯、高粱、谷子、荞麦等薯类杂粮
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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。
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。
Explainable optimized deep learning and generative AI based framework for finger millet disease detection in smart agriculture
提出融合深度学习、可解释AI与生成式AI的指状粟病害检测框架，实现高精度识别与决策支持。
AgroVisNet: A lightweight Convolutional Network and the BD-PlantDX Expert-Validated Benchmark for Radish, Potato and Pointed Gourd Disease Classification
提出轻量卷积网络AgroVisNet及专家验证的萝卜、马铃薯和尖瓜病害图像基准BD-PlantDX。
Bangladesh AI Model AgroVisNet Spots Crop Blight on Phones(轻量级 99.52% 准确率 0.46 MB 量化部署)
提出轻量网络AgroVisNet与BD-PlantDX数据集，实现手机端作物病害高精度识别。
AI 赋能杂粮智慧育种:现状、前沿与展望(华南农业大学学报 2026 年第 5 期)
综述AI赋能杂粮智慧育种的技术体系、应用案例与产业化路径。
ArXiv 2609.10469 AgroVisNet:轻量化卷积网络及萝卜-马铃薯-葫芦病害诊断基准
提出轻量卷积网络AgroVisNet及萝卜、马铃薯、葫芦病害诊断基准BD-PlantDX。
EOL-DQN: An intelligent cutting decision of potato seed tubers based on improved deep reinforcement learning
提出EOL-DQN改进深度强化学习模型，用于马铃薯种薯切块智能决策。
Explainable Deep Learning-Based Potato Leaf Disease Detection and Severity Assessment for Smart Agriculture in Bangladesh
Explainable Deep Learning-Based Potato Leaf Disease Detection and Severity Assessment for Smart Agriculture in Bangladesh。Research Square
A general Sphero-Cylindrical discrete element model of sorghum for optimising header parameters to minimise harvest losses
A general Sphero-Cylindrical discrete element model of sorghum for optimising header parameters to minimise harvest losses。Biosystems Engineering
Lightweight real-time detection of sweet potato virus disease by a hybrid CNN–Transformer network
提出Swin-SPVDNet混合CNN-Transformer网络，实现甘薯病毒病轻量级实时检测。