计算机与数字工程2024，Vol.52Issue(2)：567-571,5.DOI:10.3969/j.issn.1672-9722.2024.02.048
基于融合卷积神经网络的花卉识别方法
Flower Recognition Based on Fusion Convolution Neural Network
摘要
Abstract
Computer technologies can help people identify different kinds of plants quickly.In order to solve the difficult prob-lem of plants recognition under complex background,two kinds of flower data sets are selected as the research object with different background.Firstly,a variety of convolution neural networks are used to classify flowers with global features of flower images and find the best network.Secondly,this paper extracts effective regions of the plant image and removes the invalid regions in the image by using Mask R-CNN,which makes sure that the network following can get more accurate effective features.Finally,the best net-work is trained again with processed images.The results show that this method can improve the accuracy of plant recognition with simple background by 3%and in complex background by 5%.关键词
卷积神经网络/Mask R-CNN/花卉识别Key words
convolutional neural network/Mask R-CNN/flower recognition分类
信息技术与安全科学引用本文复制引用
段毛毛,翟睿..基于融合卷积神经网络的花卉识别方法[J].计算机与数字工程,2024,52(2):567-571,5.基金项目
克拉玛依市优秀科技创新人才基金项目(编号:XQZX20230110)资助. （编号:XQZX20230110）
