基于发育网络识别模型的大熊猫面部识别
|
摘要
个体识别是动物行为学与生态学研究工作的基础,也是制定珍稀野生动物保护政策的重要依据。为了丰富大熊猫个体识别和种群数量调查的方法,我们于2017年7月分别在四川省雅安市碧峰峡大熊猫基地和四川省汶川县耿达镇的中华大熊猫苑共计拍摄18只大熊猫个体,每只大熊猫拍摄6~13张高质量面部照片(共计131张),利用发育网络(Developmental Network)建立大熊猫面部识别模型。利用此模型对存在部分背景的大熊猫面部照片进行识别检测,得到的个体识别率为79. 41%,对完全去除背景的大熊猫面部照片进行识别检测,得到的个体识别率为58. 82%。研究表明,发育网络具有足够的大熊猫个体识别能力,不同背景比例的照片对大熊猫个体识别的实际结果具有较大的影响。随着发育网络识别模型的发展,我们建议更多的野生动物保护研究者结合这一技术深入地开展珍稀野生动物(如大熊猫)个体识别研究,逐步提高识别准确度,并应用到关键区域大规模的动物调查中。
Individual identification is basis of animal behavior and ecology research,and is also important for the development of wildlife protection policies. In order to investigate new methods of giant panda( Ailuropoda melanoleuca) individual identification and population surveying,we photographed 18 giant pandas from Bifengxia giant panda base in Ya'an and the Chinese Giant Panda Garden in Gengda,Wenchuan County,Sichuan Province in July 2017. We took high-quality facial photos of each giant panda 6-13 times for a total of 131 photographs. Using a developmental Network,we formulated a model for the facial recognition of the giant panda. We used the model to test photos which had some background features,with a successful individual recognition rate of 79. 41%. We also tested photos in which the background was completely removed,which resulted in an individual recognition rate of 58. 82%. This study shows that the developmental Network has adequate discriminatory ability for giant panda individual identification,and that the proportion of background features has severe influence on the actual results of the model. With the progress of the developmental network recognition model,we suggest that more wildlife researchers pursue this application of novel technology to conduct individual identification research of rare wildlife species such as the giant panda,gradually improve identification accuracies,and apply the model to large-scale wildlife investigations in key regions.
Individual identification is basis of animal behavior and ecology research,and is also important for the development of wildlife protection policies. In order to investigate new methods of giant panda( Ailuropoda melanoleuca) individual identification and population surveying,we photographed 18 giant pandas from Bifengxia giant panda base in Ya'an and the Chinese Giant Panda Garden in Gengda,Wenchuan County,Sichuan Province in July 2017. We took high-quality facial photos of each giant panda 6-13 times for a total of 131 photographs. Using a developmental Network,we formulated a model for the facial recognition of the giant panda. We used the model to test photos which had some background features,with a successful individual recognition rate of 79. 41%. We also tested photos in which the background was completely removed,which resulted in an individual recognition rate of 58. 82%. This study shows that the developmental Network has adequate discriminatory ability for giant panda individual identification,and that the proportion of background features has severe influence on the actual results of the model. With the progress of the developmental network recognition model,we suggest that more wildlife researchers pursue this application of novel technology to conduct individual identification research of rare wildlife species such as the giant panda,gradually improve identification accuracies,and apply the model to large-scale wildlife investigations in key regions.
引文
Crouse D,Jacobs R L,Richardson Z,Klum S,Jain A,Baden A L.2017.Lemur Face ID:a face recognition system to facilitate individual identification of lemurs.BMC Zoology,2(1):2-15.
Fang N.2017.Research and Implement of Gold Monkey Recognition based on Convolutional Neural Network.Master Thesis.Xi’an:Xidian University.(in Chinese)
Freytag A,Rodner E,Simon M,Loos A,Kühl H S,Denzler J.2016.Chimpanzee faces in the wild:Log-Euclidean CNNs for predicting identities and attributes of primates.Pattern Recognition.Springer International Publishing.
Gu J Y,Liu H,Jiang G S.2013.A review of potential techniques for identifying individual Amur tigers(panthera tigris altaica).Chinese Journal of Wildlife,34(4):229-237.(in Chinese)
He C.2016.Survey of face recognition technology.Intelligent Computer and Applications,6(5):112-114.(in Chinese)
He K,Yang Z S,Q J,He L Y,D Q,Qi D W,Bi W L,Owens J,Gu X D,Yang X Y.2016.Analyzed on the threshold value of behavior data of giant panda colleced by GPS collar.Chinese Journal of Zoology,51(2):169-175.(in Chinese)
Hull V,Zhang J,Zhou S,Huang J,Li R,Liu D,Xu W,Huang Y,Ouyang Z,Zhang H.2015.Space use by endangered giant pandas.Journal of Mammalogy,96(1):230-236.
Hu J,Hu J C,Qu Z B,Yang D L.2000.Population and age structure of giant panda in Huanglongsi Nature Reserve,Sichuan,China.Zoological Research,21(4):287-290.(in Chinese)
Hu J C,Xia L.1985.Wolong’s Giant Panda.Chengdu:Sichuan Publishing House of Science and Technology.(in Chinese)
Hou J,Yang J,Li Y J,Huang J Y,Liu D,Zhang J D.2018.Spatio-temporal distribution characteristics on spatial-temporal scale of mammals using camera traps in Wolong Nature Reserve.Journal of Nanjing Forestry University(Natural Sciences Edition),42:1-7.(in Chinese)
Huang S L,Hu D F,Chen L.2016.Study on application of passive integrated transponder(PIT)in wildlife individual identification.Chinese Journal of Wildlife,37(2):172-177.(in Chinese)
Li B V,Alibhai S,Jewell Z,Li D,Zhang H.2018.Using footprints to identify and sex giant pandas.Biological Conservation,218:83-90.
Lajevardi S M,Hussain Z M.2009.Feature extraction for facial expression recognition based on Hybrid Face Regions.Advances in E-lectrical&Computer Engineering,9(3):63-67.
Li S,Wang D J,Xiao Z S,Li S H,Wang T M,Feng L M,Wang Y.2014.Camera-trapping in wildlife research and conservation in China:review and outlook.Biodiversity Science,22(6):685-695.(in Chinese)
Ma F,Liu H J,Cheng R H.2011.Research of facial expression recognization based on facial features.Computer&Digital Engineering,39(9):111-113.(in Chinese)
Norouzzaden M S,Nguyen A,kosmala M,Swanson A,Packer C,Clune J.2017.Automatically identifying wild animals in cameratrap images with deep learning.Proceedings of the National Academy of Sciences,115(25):E5716-E5725.
Pollard K A,Blumstein D T,Griffin S C.2010.Pre-screening acoustic and other natural signatures for use in noninvasive individual identification.Journal of Applied Ecology,47(5):1103-1109.
Reng H,Hao M X,Zhang M,Li Z Q,Yang G X.2012.Study on quantitative characteristics of the national nature reserves in China.Ecological Science,31(3):225-232.(in Chinese)
Rodgers A R,Rempel R S,Abraham K F.1996.A GPS-based telemetry system.Wildlife Society Bulletin,24:559-566.
Sheng D W,He X F,Lv Y.2009.A cattle iris segmentation method based on least square principle.Journal of Image and Graphics,14(10):2132-2136.(in Chinese)
Shi X W,Zhang J D,Ouyang Z Y.2016.Research progress on population investigation methods for wild giant panda.Acta Ecological Sinica,36(23):7528-7537.(in Chinese)
State Forestry Administration.2006.The 3rd National Survey Report on Giant Panda in China.Beijing:Science Press.(in Chinese)
Tang X P,Jia J S,Wang Z C,Zhang D H,Yu Bao C,Yue J B,Gong M H,Liu Y.2015.Scheme design and main result analysis of the fouth national survey on giant pandas.Forest Resources Management,(1):11-16.(in Chinese)
Wang D S,Zheng G P.2016.Face recognition with complex background based on developmental network.Journal of Zhengzhou University(Engineering Science),37(1):19-23.(in Chinese)
Wang D S,Tan D P,Wei X Q.2017.Study of face orientation recognition based on development network.Journal of Zhengzhou University(Engineering Science),38(5):23-27.(in Chinese)
Wang J,Sun J P,Shi L,Li N,Ma Z,Meng X X.2016.Natural reserve system of China:current status,problems and prospect.China Population,Resource and Environment,26(5):270-273.(in Chinese)
Weng J Y.2012.Natural and Artificial Intelligence,Introduction to Computation Brain-Mind.Michigan:BMI Press.
Wei F W,Rao G,Li M,Fang S G,Feng Z J.2001.Molecular scatology and its application-reliability,limitation and prospect.Acta Theriologica Sinica,21(2):143-152.(in Chinese)
Wei R P,Zhang G Q,Wang P Y,Li D S,Cao J L.2003.Relation of bite size in feces with age and population number of giant panda(Ailuropoda melanoleuca).Acta Ecological Sinica,23(10):2153-2162.(in Chinese)
Xiao Z S,Li S H,Jiang G S.2014.Applications of camera trapping to wildlife surveys in China.Biodiversity Science,22(6):683-684.(in Chinese)
Xie S,Hu H.2017.Facial expression recognition with FRR-CNN.E-lectronics Letters,53(4):235-237.
Yang Z C,Chen Y,Li J S,Wang L F,Piao Y,Song Z Y,Shi K.2018.Individual identification and population size assessment for A-sian elephant based on camera-trapping techniques.Acta Theriologica Sinica,38(1):18-27.(in Chinese)
Youssif A A A,Asker W A A.2011.Automatic facial expression recognition system based on geometric and appearance features.Computer&Information Science,DOI:105539/cis.v4n2p115.
Zheng X,Owen M A,Nie Y,Hu Y,Swaisgood R R,Yan L,Wei F.2016.Individual identification of wild giant pandas from camera trap photos-a systematic and hierarchical approach.Journal of Zoology,300(4):247-256.
Zhang J,Hull V,Huang J,Zhou S,Xu W,Yang H,Mc Cnnell W,Li R,Liu D,Huang Y,Ouyang Z,Zhang H,Liu J.2015.Activity patterns of the giant panda(Ailuropoda melanoleuca).Journal of Mammalogy,96(6):2251-2259.
Zhang J D,Venassa Hull,Huang J Y,Zhou S Q,Li R G,Liu D,Huang Y,Li D S,Xu W H,Zhang H M,Liu J G,Ouyang Z Y.2011.Circadian activity pattern of giant pandas during the bamboo growing season.Acta Ecological Sinica,31(10):2655-2661.(in Chinese)
Zhang L X,Wei Z Z,Li J B,Li W J.2015.Different method for animal individual identification.Chinese Journal of Wildlife,36(4):475-478.(in Chinese)
Zhang L B,Cui S P,Huang Y J,Chen D Q,Qiao H J,Li C W,Jiang Z G.2014.Infrared camera traps in wildlife research and monitoring in China:issues and insights.Biodiversity Science,22(6):696-703.(in Chinese)
Zhao K X,Dong J.2015.Recognition of individual dairy cattle based on convolutional neural networks.Transactions of the Chinese Society of Agricultural Engineering,31(5):181-187.(in Chinese)
Zheng G P.2016.Research of Developmental Network Model Simulating the Working Mechanism of Visual Cortex.Master Thesis.Zhengzhou:Zhengzhou University.(in Chinese)
Zhu S Y,Duan F,Li S.2017.Promoting diversity inventory and monitoring of birds through the camera-trapping network in China:status,challenges and future outlook.Biodiversity Science,25(10):1114-1122.(in Chinese)
马飞,刘红娟,程荣花.2011.基于人脸五官结构特征的表情识别研究.计算机与数字工程,39(9):111-113.
王东署,郑光璞.2016.基于发育网络的复杂背景下人脸识别.郑州大学学报(工学版),37(1):19-23.
王东署,谭达佩,韦晓琴.2017.基于发育网络的人脸朝向识别研究.郑州大学学报(工学版),38(5):23-27.
王静,孙军平,石磊,李宁,马中,孟秀祥.2016.中国自然保护区建设的现状、存在问题及展望.中国人口·资源与环境,26(5):270-273.
方楠.2017.基于CNN的金丝猴面部识别研究与实现.西安:西安电子科技大学硕士学位论文.
史雪威,张晋东,欧阳志云.2016.野生大熊猫种群数量调查方法研究进展.生态学报,36(23):7528-7537.
任慧,郝梦曦,张萌,李中强,杨国祥.2012.我国国家级自然保护区数量特征研究.生态科学,31(3):225-232.
朱淑怡,段菲,李晟.2017.基于红外相机网络促进我国鸟类多样性监测:现状、问题与前景.生物多样性,25(10):1114-1122.
张晋东,Venassa Hull,黄金燕,周世强,李仁贵,刘巅,黄炎,李德生,徐卫华,张和民,刘建国,欧阳志云.2011.大熊猫取食竹笋期间的昼夜活动节律和强度.生态学报,31(10):2655-2661.
张丽霞,卫泽珍,李金邦,李文洁.2015.动物个体识别方法种种.动物学报,36(4):475-478.
张履冰,崔哨朋,黄元骏,陈代强,乔慧捷,李春旺,蒋志刚.2014.红外相机技术在我国野生动物监测中的应用:问题与限制.生物多样性,22(6):696-703.
何可,杨志松,青菁,何流洋,戴强,齐敦武,毕温磊,Jacob Owens,古晓东,杨旭煜.2016.大熊猫GPS项圈行为数据的分类阈值.动物学杂志,51(2):169-175.
何春.2016.人脸识别技术研究综述.智能计算机与应用,6(5):112-114.
杨子诚,陈颖,李俊松,王利繁,飘优,宋志勇,时坤.2018.基于红外相机技术对亚洲象个体识别和种群数量评估.兽类学报,38(1):18-27.
肖治术,李欣海,姜广顺.2014.红外相机技术在我国野生动物监测研究中的应用.生物多样性,22(6):683-684.
李晟,王大军,肖治术,李欣海,王天明,冯利民,王云.2014.红外相机技术在我国野生动物研究与保护中的应用与前景.生物多样性,22(6):685-695.
国家林业局.2006.全国第三次大熊猫调查报告.北京:科学出版社.
郑光璞.2016.模拟视觉皮层工作机制的发育网络模型研究.郑州:郑州大学硕士毕业论文.
胡锦矗,夏勒.1985.卧龙的大熊猫.成都:四川科技出版社.
胡杰,胡锦矗,屈植彪,杨冬雷.2000.黄龙大熊猫种群数量和年龄结构调查.动物学研究,21(4):287-290.
赵凯旋,东键.2015.基于卷积神经网络的奶牛个体身份识别方法.农业工程学报,31(5):181-187.
侯金,杨建,李玉杰,黄金燕,刘巅,张晋东.2018.利用红外相机调查卧龙保护区兽类资源时空分布特征.南京林业大学学报(自然科学版),42:1-7.
顾佳音,刘辉,姜广顺.2013.东北虎(Pnthera tigrisaltaica)个体识别技术研究进展.野生动物,34(4):229-237.
唐小平,贾建生,王志臣,张德辉,遇宝成,岳建兵,龚明昊,刘洋.2015.全国第四次大熊猫调查方案设计及主要结果分析.林业资源管理,(1):11-16.
黄松林,胡德夫,陈力.2016.PIT野生动物个体识别中的应用研究.野生动物学报,37(2):172-177.
盛大玮,何孝富,吕岳.2009.基于最小二乘原理的牛眼虹膜分割方法.中国图象图形学报,14(10):2132-2136.
魏荣平,张贵权,王鹏彦,李德生,曹家林.2003.大熊猫粪便中竹子咬节长短与年龄和种群数量关系.生态学报,23(10):2153-2162.
魏辅文,饶刚,李明,方盛国,冯祚建.2001.分子粪便学及其应用-可靠性、局限性和展望.兽类学报,21(2):143-152.
Fang N.2017.Research and Implement of Gold Monkey Recognition based on Convolutional Neural Network.Master Thesis.Xi’an:Xidian University.(in Chinese)
Freytag A,Rodner E,Simon M,Loos A,Kühl H S,Denzler J.2016.Chimpanzee faces in the wild:Log-Euclidean CNNs for predicting identities and attributes of primates.Pattern Recognition.Springer International Publishing.
Gu J Y,Liu H,Jiang G S.2013.A review of potential techniques for identifying individual Amur tigers(panthera tigris altaica).Chinese Journal of Wildlife,34(4):229-237.(in Chinese)
He C.2016.Survey of face recognition technology.Intelligent Computer and Applications,6(5):112-114.(in Chinese)
He K,Yang Z S,Q J,He L Y,D Q,Qi D W,Bi W L,Owens J,Gu X D,Yang X Y.2016.Analyzed on the threshold value of behavior data of giant panda colleced by GPS collar.Chinese Journal of Zoology,51(2):169-175.(in Chinese)
Hull V,Zhang J,Zhou S,Huang J,Li R,Liu D,Xu W,Huang Y,Ouyang Z,Zhang H.2015.Space use by endangered giant pandas.Journal of Mammalogy,96(1):230-236.
Hu J,Hu J C,Qu Z B,Yang D L.2000.Population and age structure of giant panda in Huanglongsi Nature Reserve,Sichuan,China.Zoological Research,21(4):287-290.(in Chinese)
Hu J C,Xia L.1985.Wolong’s Giant Panda.Chengdu:Sichuan Publishing House of Science and Technology.(in Chinese)
Hou J,Yang J,Li Y J,Huang J Y,Liu D,Zhang J D.2018.Spatio-temporal distribution characteristics on spatial-temporal scale of mammals using camera traps in Wolong Nature Reserve.Journal of Nanjing Forestry University(Natural Sciences Edition),42:1-7.(in Chinese)
Huang S L,Hu D F,Chen L.2016.Study on application of passive integrated transponder(PIT)in wildlife individual identification.Chinese Journal of Wildlife,37(2):172-177.(in Chinese)
Li B V,Alibhai S,Jewell Z,Li D,Zhang H.2018.Using footprints to identify and sex giant pandas.Biological Conservation,218:83-90.
Lajevardi S M,Hussain Z M.2009.Feature extraction for facial expression recognition based on Hybrid Face Regions.Advances in E-lectrical&Computer Engineering,9(3):63-67.
Li S,Wang D J,Xiao Z S,Li S H,Wang T M,Feng L M,Wang Y.2014.Camera-trapping in wildlife research and conservation in China:review and outlook.Biodiversity Science,22(6):685-695.(in Chinese)
Ma F,Liu H J,Cheng R H.2011.Research of facial expression recognization based on facial features.Computer&Digital Engineering,39(9):111-113.(in Chinese)
Norouzzaden M S,Nguyen A,kosmala M,Swanson A,Packer C,Clune J.2017.Automatically identifying wild animals in cameratrap images with deep learning.Proceedings of the National Academy of Sciences,115(25):E5716-E5725.
Pollard K A,Blumstein D T,Griffin S C.2010.Pre-screening acoustic and other natural signatures for use in noninvasive individual identification.Journal of Applied Ecology,47(5):1103-1109.
Reng H,Hao M X,Zhang M,Li Z Q,Yang G X.2012.Study on quantitative characteristics of the national nature reserves in China.Ecological Science,31(3):225-232.(in Chinese)
Rodgers A R,Rempel R S,Abraham K F.1996.A GPS-based telemetry system.Wildlife Society Bulletin,24:559-566.
Sheng D W,He X F,Lv Y.2009.A cattle iris segmentation method based on least square principle.Journal of Image and Graphics,14(10):2132-2136.(in Chinese)
Shi X W,Zhang J D,Ouyang Z Y.2016.Research progress on population investigation methods for wild giant panda.Acta Ecological Sinica,36(23):7528-7537.(in Chinese)
State Forestry Administration.2006.The 3rd National Survey Report on Giant Panda in China.Beijing:Science Press.(in Chinese)
Tang X P,Jia J S,Wang Z C,Zhang D H,Yu Bao C,Yue J B,Gong M H,Liu Y.2015.Scheme design and main result analysis of the fouth national survey on giant pandas.Forest Resources Management,(1):11-16.(in Chinese)
Wang D S,Zheng G P.2016.Face recognition with complex background based on developmental network.Journal of Zhengzhou University(Engineering Science),37(1):19-23.(in Chinese)
Wang D S,Tan D P,Wei X Q.2017.Study of face orientation recognition based on development network.Journal of Zhengzhou University(Engineering Science),38(5):23-27.(in Chinese)
Wang J,Sun J P,Shi L,Li N,Ma Z,Meng X X.2016.Natural reserve system of China:current status,problems and prospect.China Population,Resource and Environment,26(5):270-273.(in Chinese)
Weng J Y.2012.Natural and Artificial Intelligence,Introduction to Computation Brain-Mind.Michigan:BMI Press.
Wei F W,Rao G,Li M,Fang S G,Feng Z J.2001.Molecular scatology and its application-reliability,limitation and prospect.Acta Theriologica Sinica,21(2):143-152.(in Chinese)
Wei R P,Zhang G Q,Wang P Y,Li D S,Cao J L.2003.Relation of bite size in feces with age and population number of giant panda(Ailuropoda melanoleuca).Acta Ecological Sinica,23(10):2153-2162.(in Chinese)
Xiao Z S,Li S H,Jiang G S.2014.Applications of camera trapping to wildlife surveys in China.Biodiversity Science,22(6):683-684.(in Chinese)
Xie S,Hu H.2017.Facial expression recognition with FRR-CNN.E-lectronics Letters,53(4):235-237.
Yang Z C,Chen Y,Li J S,Wang L F,Piao Y,Song Z Y,Shi K.2018.Individual identification and population size assessment for A-sian elephant based on camera-trapping techniques.Acta Theriologica Sinica,38(1):18-27.(in Chinese)
Youssif A A A,Asker W A A.2011.Automatic facial expression recognition system based on geometric and appearance features.Computer&Information Science,DOI:105539/cis.v4n2p115.
Zheng X,Owen M A,Nie Y,Hu Y,Swaisgood R R,Yan L,Wei F.2016.Individual identification of wild giant pandas from camera trap photos-a systematic and hierarchical approach.Journal of Zoology,300(4):247-256.
Zhang J,Hull V,Huang J,Zhou S,Xu W,Yang H,Mc Cnnell W,Li R,Liu D,Huang Y,Ouyang Z,Zhang H,Liu J.2015.Activity patterns of the giant panda(Ailuropoda melanoleuca).Journal of Mammalogy,96(6):2251-2259.
Zhang J D,Venassa Hull,Huang J Y,Zhou S Q,Li R G,Liu D,Huang Y,Li D S,Xu W H,Zhang H M,Liu J G,Ouyang Z Y.2011.Circadian activity pattern of giant pandas during the bamboo growing season.Acta Ecological Sinica,31(10):2655-2661.(in Chinese)
Zhang L X,Wei Z Z,Li J B,Li W J.2015.Different method for animal individual identification.Chinese Journal of Wildlife,36(4):475-478.(in Chinese)
Zhang L B,Cui S P,Huang Y J,Chen D Q,Qiao H J,Li C W,Jiang Z G.2014.Infrared camera traps in wildlife research and monitoring in China:issues and insights.Biodiversity Science,22(6):696-703.(in Chinese)
Zhao K X,Dong J.2015.Recognition of individual dairy cattle based on convolutional neural networks.Transactions of the Chinese Society of Agricultural Engineering,31(5):181-187.(in Chinese)
Zheng G P.2016.Research of Developmental Network Model Simulating the Working Mechanism of Visual Cortex.Master Thesis.Zhengzhou:Zhengzhou University.(in Chinese)
Zhu S Y,Duan F,Li S.2017.Promoting diversity inventory and monitoring of birds through the camera-trapping network in China:status,challenges and future outlook.Biodiversity Science,25(10):1114-1122.(in Chinese)
马飞,刘红娟,程荣花.2011.基于人脸五官结构特征的表情识别研究.计算机与数字工程,39(9):111-113.
王东署,郑光璞.2016.基于发育网络的复杂背景下人脸识别.郑州大学学报(工学版),37(1):19-23.
王东署,谭达佩,韦晓琴.2017.基于发育网络的人脸朝向识别研究.郑州大学学报(工学版),38(5):23-27.
王静,孙军平,石磊,李宁,马中,孟秀祥.2016.中国自然保护区建设的现状、存在问题及展望.中国人口·资源与环境,26(5):270-273.
方楠.2017.基于CNN的金丝猴面部识别研究与实现.西安:西安电子科技大学硕士学位论文.
史雪威,张晋东,欧阳志云.2016.野生大熊猫种群数量调查方法研究进展.生态学报,36(23):7528-7537.
任慧,郝梦曦,张萌,李中强,杨国祥.2012.我国国家级自然保护区数量特征研究.生态科学,31(3):225-232.
朱淑怡,段菲,李晟.2017.基于红外相机网络促进我国鸟类多样性监测:现状、问题与前景.生物多样性,25(10):1114-1122.
张晋东,Venassa Hull,黄金燕,周世强,李仁贵,刘巅,黄炎,李德生,徐卫华,张和民,刘建国,欧阳志云.2011.大熊猫取食竹笋期间的昼夜活动节律和强度.生态学报,31(10):2655-2661.
张丽霞,卫泽珍,李金邦,李文洁.2015.动物个体识别方法种种.动物学报,36(4):475-478.
张履冰,崔哨朋,黄元骏,陈代强,乔慧捷,李春旺,蒋志刚.2014.红外相机技术在我国野生动物监测中的应用:问题与限制.生物多样性,22(6):696-703.
何可,杨志松,青菁,何流洋,戴强,齐敦武,毕温磊,Jacob Owens,古晓东,杨旭煜.2016.大熊猫GPS项圈行为数据的分类阈值.动物学杂志,51(2):169-175.
何春.2016.人脸识别技术研究综述.智能计算机与应用,6(5):112-114.
杨子诚,陈颖,李俊松,王利繁,飘优,宋志勇,时坤.2018.基于红外相机技术对亚洲象个体识别和种群数量评估.兽类学报,38(1):18-27.
肖治术,李欣海,姜广顺.2014.红外相机技术在我国野生动物监测研究中的应用.生物多样性,22(6):683-684.
李晟,王大军,肖治术,李欣海,王天明,冯利民,王云.2014.红外相机技术在我国野生动物研究与保护中的应用与前景.生物多样性,22(6):685-695.
国家林业局.2006.全国第三次大熊猫调查报告.北京:科学出版社.
郑光璞.2016.模拟视觉皮层工作机制的发育网络模型研究.郑州:郑州大学硕士毕业论文.
胡锦矗,夏勒.1985.卧龙的大熊猫.成都:四川科技出版社.
胡杰,胡锦矗,屈植彪,杨冬雷.2000.黄龙大熊猫种群数量和年龄结构调查.动物学研究,21(4):287-290.
赵凯旋,东键.2015.基于卷积神经网络的奶牛个体身份识别方法.农业工程学报,31(5):181-187.
侯金,杨建,李玉杰,黄金燕,刘巅,张晋东.2018.利用红外相机调查卧龙保护区兽类资源时空分布特征.南京林业大学学报(自然科学版),42:1-7.
顾佳音,刘辉,姜广顺.2013.东北虎(Pnthera tigrisaltaica)个体识别技术研究进展.野生动物,34(4):229-237.
唐小平,贾建生,王志臣,张德辉,遇宝成,岳建兵,龚明昊,刘洋.2015.全国第四次大熊猫调查方案设计及主要结果分析.林业资源管理,(1):11-16.
黄松林,胡德夫,陈力.2016.PIT野生动物个体识别中的应用研究.野生动物学报,37(2):172-177.
盛大玮,何孝富,吕岳.2009.基于最小二乘原理的牛眼虹膜分割方法.中国图象图形学报,14(10):2132-2136.
魏荣平,张贵权,王鹏彦,李德生,曹家林.2003.大熊猫粪便中竹子咬节长短与年龄和种群数量关系.生态学报,23(10):2153-2162.
魏辅文,饶刚,李明,方盛国,冯祚建.2001.分子粪便学及其应用-可靠性、局限性和展望.兽类学报,21(2):143-152.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |