Mobile phone recognition method based on bilinear convolutional neural network  

作　　者：HAN HongGui ZHEN Qi YANG HongYan DU YongPing QIAO JunFei 

机构地区：[1]Faculty of Information Technology,Beijing University of Technology,Beijing 100124,China

出　　处：《Science China(Technological Sciences)》2021年第11期2477-2484,共8页中国科学（技术科学英文版）

基　　金：supported by the National Key Program of China(Grant No.2018YFC1900800-5);the National Natural Science Foundation of China(Grant Nos.61890930-5 and 61622301);the Beijing University Outstanding Young Scientist Program(Grant No.BJJWZYJH0120191000-5020)。

摘　　要：Model recognition of second-hand mobile phones has been considered as an essential process to improve the efficiency of phone recycling. However, due to the diversity of mobile phone appearances, it is difficult to realize accurate recognition. To solve this problem, a mobile phone recognition method based on bilinear-convolutional neural network(B-CNN) is proposed in this paper.First, a feature extraction model, based on B-CNN, is designed to adaptively extract local features from the images of secondhand mobile phones. Second, a joint loss function, constructed by center distance and softmax, is developed to reduce the interclass feature distance during the training process. Third, a parameter downscaling method, derived from the kernel discriminant analysis algorithm, is introduced to eliminate redundant features in B-CNN. Finally, the experimental results demonstrate that the B-CNN method can achieve higher accuracy than some existing methods.

关 键 词：bilinear convolutional neural network low-rank decomposition joint loss fine-grained image recognition 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—控制科学与工程]