{"id":"https://openalex.org/W2915348692","doi":"https://doi.org/10.1109/wacvw50321.2020.9096925","title":"Similarity Learning Networks for Animal Individual Re-Identification - Beyond the Capabilities of a Human Observer","display_name":"Similarity Learning Networks for Animal Individual Re-Identification - Beyond the Capabilities of a Human Observer","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W2915348692","doi":"https://doi.org/10.1109/wacvw50321.2020.9096925","mag":"2915348692"},"language":"en","primary_location":{"id":"doi:10.1109/wacvw50321.2020.9096925","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacvw50321.2020.9096925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Applications of Computer Vision Workshops (WACVW)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1902.09324","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018258698","display_name":"Stefan Schneider","orcid":"https://orcid.org/0000-0002-6903-6605"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Stefan Schneider","raw_affiliation_strings":["School of Computer Science, University of Guelph"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Guelph","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102922725","display_name":"Graham W. Taylor","orcid":"https://orcid.org/0000-0001-5867-3652"},"institutions":[{"id":"https://openalex.org/I4210127509","display_name":"Vector Institute","ror":"https://ror.org/03kqdja62","country_code":"CA","type":"facility","lineage":["https://openalex.org/I4210127509"]},{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Graham W. Taylor","raw_affiliation_strings":["School of Engineering, University of Guelph Vector Institute for Artificial Intelligence"],"affiliations":[{"raw_affiliation_string":"School of Engineering, University of Guelph Vector Institute for Artificial Intelligence","institution_ids":["https://openalex.org/I4210127509","https://openalex.org/I79817857"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053492737","display_name":"Stefan C. Kremer","orcid":"https://orcid.org/0000-0002-3667-4379"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Stefan C. Kremer","raw_affiliation_strings":["School of Computer Science, University of Guelph"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Guelph","institution_ids":["https://openalex.org/I79817857"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018258698"],"corresponding_institution_ids":["https://openalex.org/I79817857"],"apc_list":null,"apc_paid":null,"fwci":0.4907,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.6434258,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"44","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10199","display_name":"Wildlife Ecology and Conservation","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11665","display_name":"Animal Vocal Communication and Behavior","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/1309","display_name":"Developmental Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7105916142463684},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.645015299320221},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6078168153762817},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.606779932975769},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6040221452713013},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5358203053474426},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5331173539161682},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5322100520133972},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47806599736213684},{"id":"https://openalex.org/keywords/animal-species","display_name":"Animal species","score":0.4624604880809784},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.46224287152290344},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41461458802223206},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3348861336708069},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.20767197012901306},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.14681276679039001},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14060255885124207},{"id":"https://openalex.org/keywords/evolutionary-biology","display_name":"Evolutionary biology","score":0.0940314531326294}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7105916142463684},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.645015299320221},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6078168153762817},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.606779932975769},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6040221452713013},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5358203053474426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5331173539161682},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5322100520133972},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47806599736213684},{"id":"https://openalex.org/C2993056352","wikidata":"https://www.wikidata.org/wiki/Q7432","display_name":"Animal species","level":2,"score":0.4624604880809784},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.46224287152290344},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41461458802223206},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3348861336708069},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.20767197012901306},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.14681276679039001},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14060255885124207},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0940314531326294},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/wacvw50321.2020.9096925","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacvw50321.2020.9096925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Applications of Computer Vision Workshops (WACVW)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1902.09324","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1902.09324","pdf_url":"https://arxiv.org/pdf/1902.09324","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2915348692","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1902.09324","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1902.09324","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1902.09324","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1902.09324","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1902.09324","pdf_url":"https://arxiv.org/pdf/1902.09324","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2915348692.pdf","grobid_xml":"https://content.openalex.org/works/W2915348692.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1686810756","https://openalex.org/W1969860370","https://openalex.org/W1981302151","https://openalex.org/W2009907187","https://openalex.org/W2022087710","https://openalex.org/W2024922353","https://openalex.org/W2047028564","https://openalex.org/W2055032654","https://openalex.org/W2064917021","https://openalex.org/W2065788615","https://openalex.org/W2095705004","https://openalex.org/W2096733369","https://openalex.org/W2099034710","https://openalex.org/W2100020371","https://openalex.org/W2127589108","https://openalex.org/W2138621090","https://openalex.org/W2145287260","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2204750386","https://openalex.org/W2295675274","https://openalex.org/W2300445845","https://openalex.org/W2514319263","https://openalex.org/W2598634450","https://openalex.org/W2599765304","https://openalex.org/W2746791238","https://openalex.org/W2751269321","https://openalex.org/W2768765894","https://openalex.org/W2798827285","https://openalex.org/W2802043043","https://openalex.org/W2919115771","https://openalex.org/W2949117887","https://openalex.org/W2949431458","https://openalex.org/W2951690425","https://openalex.org/W2962837037","https://openalex.org/W2963163009","https://openalex.org/W2963413044","https://openalex.org/W2963446712","https://openalex.org/W2963556638","https://openalex.org/W2963775347","https://openalex.org/W3093326439","https://openalex.org/W3099206234","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6735463952","https://openalex.org/W6735531217","https://openalex.org/W6746043372","https://openalex.org/W6764371201"],"related_works":["https://openalex.org/W2989926381","https://openalex.org/W2581974582","https://openalex.org/W3160423595","https://openalex.org/W2889709299","https://openalex.org/W2336431778","https://openalex.org/W2896652510","https://openalex.org/W2972552825","https://openalex.org/W1497143081","https://openalex.org/W3090990827","https://openalex.org/W3126015239","https://openalex.org/W2908944636","https://openalex.org/W2922241966","https://openalex.org/W3114830698","https://openalex.org/W3183891330","https://openalex.org/W3199145413","https://openalex.org/W3139531396","https://openalex.org/W2950683722","https://openalex.org/W2982285030","https://openalex.org/W2511423172","https://openalex.org/W2953302097"],"abstract_inverted_index":{"Deep":[0],"learning":[1,25,32],"has":[2],"become":[3],"the":[4,80,92,124,199,225,241],"standard":[5],"methodology":[6],"to":[7,28,67,86,99,145,208,250],"approach":[8],"computer":[9,57],"vision":[10,58],"tasks":[11,33],"when":[12],"large":[13],"amounts":[14],"of":[15,56,82,94,164,196,201,222,227,243],"labeled":[16],"data":[17,142],"are":[18,240],"available.":[19],"One":[20,48],"area":[21],"where":[22,34],"traditional":[23],"deep":[24,95],"approaches":[26],"fail":[27],"perform":[29],"is":[30,51,215,235],"one-shot":[31],"a":[35,40,65,191,219,244],"model":[36],"must":[37],"correctly":[38],"classify":[39],"new":[41],"category":[42],"after":[43],"seeing":[44],"only":[45],"one":[46],"example.":[47],"such":[49],"domain":[50],"animal":[52,87,107,202,211,252],"re-identification,":[53,88],"an":[54,210],"application":[55,81],"which":[59],"can":[60,189],"be":[61],"used":[62],"globally":[63],"as":[64,89,91],"method":[66],"automate":[68],"species":[69],"population":[70,228],"estimates":[71],"from":[72,254],"camera":[73,255],"trap":[74,256],"images.":[75],"Our":[76,233],"work":[77],"demonstrates":[78],"both":[79],"similarity":[83,116,186,237],"comparison":[84,117,187,238],"networks":[85,98,188,239],"well":[90],"capabilities":[93],"convolutional":[96],"neural":[97],"generalize":[100],"across":[101,110],"domains.":[102],"Few":[103],"studies":[104],"have":[105],"considered":[106],"re-identification":[108,253],"methods":[109],"species.":[111,177],"Here,":[112],"we":[113],"compare":[114],"two":[115],"methodologies:":[118],"Siamese":[119,173],"and":[120,129,137,155,230],"Triplet-Loss,":[121],"based":[122],"on":[123],"AlexNet,":[125],"VGG-19,":[126],"DenseNet201,":[127],"MobileNetV2,":[128],"InceptionV3":[130],"architectures":[131],"considering":[132],"mean":[133],"average":[134],"precision":[135],"(mAP)@1":[136],"mAP@5.":[138],"We":[139,166],"consider":[140],"five":[141,146],"sets":[143],"corresponding":[144],"different":[147],"species:":[148],"humans,":[149],"chimpanzees,":[150],"humpback":[151],"whales,":[152],"fruit":[153],"flies,":[154],"Siberian":[156],"tigers,":[157],"each":[158],"with":[159],"their":[160],"own":[161],"unique":[162],"set":[163],"challenges.":[165],"demonstrate":[167,184],"that":[168,185,195,236,247],"Triplet":[169],"Loss":[170],"outperformed":[171],"its":[172],"counterpart":[174],"for":[175,198,206,217],"all":[176],"Without":[178],"any":[179],"species-specific":[180],"modifications,":[181],"our":[182],"results":[183],"reach":[190],"performance":[192],"level":[193],"beyond":[194],"humans":[197],"task":[200],"re-identification.":[203],"The":[204],"ability":[205],"researchers":[207],"re-identify":[209],"individual":[212],"upon":[213],"re-encounter":[214],"fundamental":[216],"addressing":[218],"broad":[220],"range":[221],"questions":[223],"in":[224],"study":[226],"dynamics":[229],"community/behavioural":[231],"ecology.":[232],"expectation":[234],"beginning":[242],"major":[245],"trend":[246],"could":[248],"stand":[249],"revolutionize":[251],"data.":[257]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2025-10-10T00:00:00"}