黑龙江畜牧兽医Issue(6)：55-62,8.DOI:10.13881/j.cnki.hljxmsy.2025.11.0124
基于多尺度特征融合增强的InceptionResNetV1模型的牦牛面部识别
Yak face recognition based on enhanced InceptionResNetV1 model with multiscale feature fusion
摘要
Abstract
In order to solve the problems of low efficiency in manual recording,easy loss of physical labels,and difficulty in insurance claim assessment in traditional yak identity management,this study proposed a yak face recognition method named YakFaceInception.This model introduced a feature pyramid network(FPN)of improved smooth module at the neck of the InceptionResNetV1 model to facilitate multi-scale feature fusion.The input yak facial image was mapped into 512-dimensional feature vectors through a model,and then the cosine similarity between the feature vectors was calculated to determine whether they belong to the same yak.The results showed that the YakFaceInception model achieved a recall rate of 92.9%,which was slightly lower than that of the ArcFaceNet model.However,its precision,F1 score,and model size were all superior to those of ArcFaceNet,ResidualAttentionNet,Cbam_ResNet_50,MobileFaceNet,and ResNet50.The YakFaceInception model had a recall rate of 92.9%,an accuracy rate of 96.8%,an F1 score of 94.8,and a model size of 115.5 Mb on the test set of the self-built original yak facial dataset.Compared with the original InceptionResNetV1,the recall rate,accuracy rate,F1 score,and model size were increased by 0.54%,1.57%,1.07%,and 391.49%,respectively.The results indicated that comprehensive performance of YakFaceInception model was better than that of InceptionResNetV1 model,and the prediction of the model tends to be conservative.关键词
牦牛/面部识别/面部检测/多尺度特征融合/智慧养殖Key words
yak/face detection/face recognition/multi-scale feature fusion/smart farming分类
农业科技引用本文复制引用
张梓烨,高红梅,高定国,乔晶晶..基于多尺度特征融合增强的InceptionResNetV1模型的牦牛面部识别[J].黑龙江畜牧兽医,2026,(6):55-62,8.基金项目
国家自然科学基金项目(62166038) （62166038）
国家高层次人才特殊支持计划资助项目 （）
西藏大学人才发展激励计划项目 （）
