基于一维残差卷积的烟叶分级方法研究OACSTPCD
Research on tobacco grade classification based on one-dimensional residual convolution
在烟叶分级过程中,由于人为主观性、分级标准不一致等因素导致分级结果不一致.针对以上问题,提出一种一维残差卷积的烟叶等级分类模型.首先,改进VGG16网络,将方形矩阵卷积核和池化窗口改为适应于一维光谱数据的向量卷积核和池化窗口.然后,利用BasicBlock残差模块替换多层卷积叠加的结构,对光谱数据进行更深层的提取,防止梯度消失问题.最后,在卷积层后面接入BN层模块,通过归一化的方式,防止卷积计算后由于数据分布分散而导致的网络效率降低问题.选取B2…查看全部>>
In the tobacco grading process,inconsistent grading results are often observed due to factors such as human subjectivity and inconsistent grading standards.To address these issues,a tobacco grade classification model based on one-dimensional residual convolution is proposed.The VGG16 network is improved by replacing the square matrix convolutional kernels and pooling windows with vector convolution kernel and pooling window suitable for one-dimensional spect…查看全部>>
孙祥洪;罗智勇
江西中烟工业有限责任公司 技术中心, 江西 南昌 330096青岛科技大学 信息科学技术学院, 山东 青岛 266061
电子信息工程
烟叶分级残差卷积神经网络残差模块近红外光谱数据特征提取数据采集
tobacco gradingresidual convolutional neural networkresidual modulenear infrared spectroscopydata feature extractiondata acquisition
《现代电子技术》 2024 (2)
165-170,6
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