From frame-wise detection to instance-level tracking: robust crop row perception for autonomous paddy field navigation
提出从逐帧检测到实例级跟踪的作物行感知方法，用于水稻田自主导航。
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#稻田识别
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未标这个词，内容接近Hybrid Rule-Based and Machine Learning Decision-Support Framework for Smart Paddy Farming
提出规则与机器学习混合的水稻决策支持框架，提升决策精度并节水增产。
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Comparative evaluation of classical machine learning and deep learning models for early weed detection in precision agriculture
对比经典机器学习与深度学习模型在精准农业早期杂草检测中的性能。
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Multi-scale lodging in rice and wheat: bridging biomechanical traits, phenotypic detection, and intelligent harvesting systems
综述构建了水稻小麦倒伏从分子到收获的跨尺度力学框架，连接生物力学性状、表型检测与智能收获。
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Rice Cropping Pattern Mapping Using GEE-Based Sentinel-1/2 Time-Series Imagery and Machine Learning
基于GEE融合Sentinel-1/2时序与地形特征，用机器学习高精度制图长三角水稻种植模式。
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A data-centric multi-modal ai framework for weed detection and classification in smart agriculture
A data-centric multi-modal ai framework for weed detection and classification in smart agriculture。Discover Applied Sciences
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Deep learning-based classification of wet direct seeded rice, broadcasted direct seeded rice and transplanted rice using drone imagery for precision agriculture
用无人机可见光影像和深度学习模型区分直播稻、湿直播稻与移栽稻三种水稻种植方式。
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基于无人机多光谱图像和VGG21模型的小麦渍害调控效果识别方法
用无人机多光谱图像和VGG21模型识别小麦渍害调控效果。
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