华南农业大学学报2026，Vol.47Issue(4)：638-648,11.DOI:10.7671/j.issn.1001-411X.202509029
基于SMA-DeepLab的荔枝秋冬梢低空遥感分割模型
A low-altitude remote sensing segmentation model for litchi autumn-winter shoots based on SMA-DeepLab
摘要
Abstract
[Objective]Litchi is one of the most representative characteristic fruit trees in the Lingnan region,and the management of its autumn and winter shoots as well as nutrient regulation is directly related to fruit trees yield.Affected by climatic conditions and the vertical canopy structure of the tree crown,litchi trees are prone to apical flushing and asynchronous shoot emergence of autumn and winter shoots,resulting in nutrient waste.Therefore,achieving accurate segmentation of litchi autumn and winter shoots provides a critical basis for subsequent precision management.[Method]First,high-resolution images of litchi autumn and winter shoots were acquired via low-altitude UAVs over two years.Second,the SMA-DeepLab model was proposed for accurate segmentation of litchi autumn and winter shoots.In this model,the backbone network of DeepLabv3+was replaced with SMANet.The main network of SMANet improved feature quality through StarNet and integrated features with the adaptive spatial feature fusion(ASFF)module for multi-scale feature fusion.Meanwhile,a receptive field aggregator(RFA)was introduced to enhance boundary precision.[Result]In terms of accuracy performance,the mean pixel accuracy(mPA)and mean intersection over union(mIoU)were 93.46%and 87.84%,respectively,representing improvements of 2.74 and 2.75 percentage points compared with the baseline model.In terms of efficiency,the floating-point operations per second(FLOPS)and frames per second(FPS)were 111.44 and 31.63,respectively,and the number of parameters was reduced by 51.3%compared with the baseline model.In addition,visualization of segmentation results showed that the proposed model achieved accurate segmentation of slender shoots and motion-blurred regions when facing interfering factors like complex backgrounds.[Conclusion]The SMA-DeepLab model proposed in this study provides an effective solution for the segmentation of litchi autumn and winter shoots and serves as a technical reference for other objects segmentation tasks in the field of smart agriculture.关键词
无人机遥感/图像分割/深度学习/荔枝秋冬梢Key words
UAV remote sensing/Image segmentation/Deep learning/Litchi autumn-winter shoot分类
农业科技引用本文复制引用
沈梓凡,兰玉彬,邓小玲,孙贺光,徐睿,王一伟,韩博,李昌生,刘卓,麦焕明,邱晧烽..基于SMA-DeepLab的荔枝秋冬梢低空遥感分割模型[J].华南农业大学学报,2026,47(4):638-648,11.基金项目
国家自然科学基金(32371984) （32371984）
广东省重点研发计划(2023B0202090001) （2023B0202090001）
广东省高校重点领域专项(2019KZDZX1012) （2019KZDZX1012）
