计算机与数字工程2024，Vol.52Issue(5)：1406-1411,6.DOI:10.3969/j.issn.1672-9722.2024.05.025
基于特征增强和分组模块的车型精细识别
Fine Vehicle Recognition Based on Feature Enhancement and Grouping Module
摘要
Abstract
In order to solve the problems of many types of vehicles,small differences,complex models and low recognition ac-curacy,a fine vehicle recognition method based on feature enhancement and grouping module is proposed,which is improved on the basis of ResNet network.The attention mechanism of multi-scale channel domain and spatial domain is added to the convolution block to enhance the extraction of important features,and the multi-channel feature graphs are grouped and continuously optimized according to the grouping loss function.KL(Kullback-Leibler)divergence loss function and cross entropy loss function are com-bined by weighted method.The method is tested on Stanford cars-196 dataset and self-made dataset to verify the effectiveness of the proposed model.关键词
车型精细识别/多尺度/注意力机制/特征增强/损失函数Key words
fine vehicle identification/multi-scale/attention mechanism/feature enhancement/loss function分类
信息技术与安全科学引用本文复制引用
郑秋梅,曹文龙,王风华..基于特征增强和分组模块的车型精细识别[J].计算机与数字工程,2024,52(5):1406-1411,6.基金项目
国家自然科学基金项目(编号:52074341,51874340)资助. （编号:52074341,51874340）
