基于深度学习的图像微小特征识别技术
Image Micro-feature Recognition Technology Based on Deep Learning
乔松霞1
作者信息
- 1. 郑州交通技师学院,河南 郑州 450016
- 折叠
摘要
为了提高对图像中微小特征的识别效果,本研究基于深度学习技术,提出了一种新的特征识别技术.首先,对采集到的原始图像进行小波分解处理,消除噪声对图像质量的影响;然后,基于图像预处理结果,利用深度学习技术中的空间注意力机制,构建图像识别注意力模型;最后,通过设定模型训练过程,实现对图像中微小特征的识别.实验结果表明:应用此技术后,对图像微小特征的识别精度始终保持在 98.00%以上,且此技术降低了识别计算量.
Abstract
In order to improve the recognition effect of micro-features in images,a new feature recognition technology is proposed based on deep learning technology.Firstly,the original image is decomposed by wavelet to eliminate the influence of noise on image quality;then,based on the results of image pre-processing,the attention model of image recognition is constructed by using the spatial attention mechanism in deep learning technology;finally,by setting the training process of the model,the recognition of micro-features in the image is realized.The experimental results show that after applying this technology,the recognition accuracy of image micro-features is always above 98.00%,and this technology reduces the recognition calculation.
关键词
图像处理/特征识别/深度学习/注意力机制Key words
image processing/feature recognition/deep learning/attention mechanism引用本文复制引用
出版年
2024
NETL
NSTL
万方数据