Amur tiger stripes:individual identification based on deep convolutional neural network
作者机构:Department of MathematicsSchool of ScienceNortheast Forestry UniversityHarbinChina Feline Research CenterNational Forestry and Grassland AdministrationCollege of Wildlife and Protected AreasNortheast Forestry UniversityHarbinChina Siberian Tiger ParkHarbinHeilongjiangChina
出 版 物:《Integrative Zoology》 (整合动物学(英文版))
年 卷 期:2020年第15卷第6期
页 面:461-470页
核心收录:
学科分类:0710[理学-生物学] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 0905[农学-畜牧学] 081104[工学-模式识别与智能系统] 08[工学] 0906[农学-兽医学] 0835[工学-软件工程] 071002[理学-动物学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:the Fundamental Research Funds for the Central Universities(2572018BC07,2572017PZ14) the Heilongjiang postdoctoral project fund project(LBH-Z18003) Biodiversity Survey,Monitoring and Assessment Project of Ministry of Ecology and Environment,China(2019HB2096001006) the National Natural Science Foundation of China(NSFC 31872241,31572285) the Individual Identification Technological Research on Camera-trapping images of Amur tigers(NFGA 2017)
主 题:Amur tiger deep convolutional neural network individual identification stripe feature
摘 要:The automatic individual identification of Amur tigers(Panthera tigris altaica)is important for population monitoring and making effective conservation *** existing research primarily relies on manual identifi-cation,which does not scale well to large *** this paper,the deep convolution neural networks algorithm is constructed to implement the automatic individual identification for large numbers of Amur tiger *** experimental data were obtained from 40 Amur tigers in Tieling Guaipo Tiger Park,*** number of images collected from each tiger was approximately 200,and a total of 8277 images were *** experiments were carried out on both the left and right side of *** results suggested that the recognition accuracy rate of left and right sides are 90.48%and 93.5%,*** accuracy of our network has achieved the similar level compared to other state of the art networks like LeNet,ResNet34,and ZF_*** running time is much shorter than that of other ***,this study can provide a new approach on automatic individual identification technology in the case of the Amur tiger.