基于改进Mask R-CNN的小麦在穗籽粒表型参数测试方法OA北大核心CSTPCD
A Method for Testing Phenotype Parameters of Wheat Grains on Spike Based on Improved Mask R-CNN
[目的]针对小麦籽粒性状参数获取需要脱粒后测量,测量程序繁杂、费时费力的缺点,提出基于深度学习的小麦在穗籽粒表型参数测试方法.[方法]采集镇麦25、宁麦13和农麦88这3个品种小麦穗两侧正视图像,利用小麦穗正视图像构建图像增强数据集,提出深度学习与形态学处理相结合的小麦在穗籽粒表型参数测试方法.首先,建立基于改进MaskR-CNN网络的麦穗颖壳分割模型,模型以ResNet和FNP为特征提取网络并引入坐标注意力(CA)模块、聚合模块和半卷积模块,实…查看全部>>
[Objective]Wheat grain phenotype parameters were tested after grains only must been threshed by combine,this process was time-consuming,laborious and complicate.Therefore,a method to test morphological parameters of wheat grains on spike based on improved Mask R-CNN was proposed in this research.[Method]Two sides front images of three varieties wheat spikes,including Zhenmai 25,Ningmai 13 and Longmai 88(Early maturity variety),were collected,and then the ima…查看全部>>
王赟赟;李毅念;陈玉仑;丁启朔;何瑞银
南京农业大学工学院,南京 210031南京农业大学工学院,南京 210031南京农业大学工学院,南京 210031南京农业大学工学院,南京 210031南京农业大学工学院,南京 210031
麦穗籽粒表型深度学习坐标注意力
wheat spikegrain phenotypedeep learningCoordinate Attention
《中国农业科学》 2024 (12)
2322-2335,14
国家重点研发计划(2022YFD2300703、2022YFD2300304)、中央高校基本科研业务费专项资金资助项目(KYYJ202106)
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