{"id":"https://openalex.org/W3114959606","doi":"https://doi.org/10.1109/ivcnz51579.2020.9290558","title":"Deep Sheep: kinship assignment in livestock from facial images","display_name":"Deep Sheep: kinship assignment in livestock from facial images","publication_year":2020,"publication_date":"2020-11-25","ids":{"openalex":"https://openalex.org/W3114959606","doi":"https://doi.org/10.1109/ivcnz51579.2020.9290558","mag":"3114959606"},"language":"en","primary_location":{"id":"doi:10.1109/ivcnz51579.2020.9290558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivcnz51579.2020.9290558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025970904","display_name":"Lech Szymanski","orcid":"https://orcid.org/0000-0002-5192-0304"},"institutions":[{"id":"https://openalex.org/I80281795","display_name":"University of Otago","ror":"https://ror.org/01jmxt844","country_code":"NZ","type":"education","lineage":["https://openalex.org/I80281795"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Lech Szymanski","raw_affiliation_strings":["University of Otago, Dunedin, New Zealand"],"affiliations":[{"raw_affiliation_string":"University of Otago, Dunedin, New Zealand","institution_ids":["https://openalex.org/I80281795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100429794","display_name":"Michael Lee","orcid":"https://orcid.org/0000-0001-7538-0720"},"institutions":[{"id":"https://openalex.org/I80281795","display_name":"University of Otago","ror":"https://ror.org/01jmxt844","country_code":"NZ","type":"education","lineage":["https://openalex.org/I80281795"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Michael Lee","raw_affiliation_strings":["University of Otago, Dunedin, New Zealand"],"affiliations":[{"raw_affiliation_string":"University of Otago, Dunedin, New Zealand","institution_ids":["https://openalex.org/I80281795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025970904"],"corresponding_institution_ids":["https://openalex.org/I80281795"],"apc_list":null,"apc_paid":null,"fwci":0.3908,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.63166297,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.989300012588501,"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/T11448","display_name":"Face recognition and analysis","score":0.989300012588501,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9573000073432922,"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/T10594","display_name":"Genetic and phenotypic traits in livestock","score":0.9110000133514404,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/kinship","display_name":"Kinship","score":0.8751448392868042},{"id":"https://openalex.org/keywords/livestock","display_name":"Livestock","score":0.7717057466506958},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6630786061286926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6434459090232849},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6315876245498657},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5208050012588501},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46622422337532043},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4297787547111511},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41407281160354614},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4135807752609253},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.392017662525177},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34846389293670654},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.23463964462280273},{"id":"https://openalex.org/keywords/anthropology","display_name":"Anthropology","score":0.11492812633514404},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.10510510206222534},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07793256640434265},{"id":"https://openalex.org/keywords/social-science","display_name":"Social science","score":0.07165509462356567}],"concepts":[{"id":"https://openalex.org/C144348335","wikidata":"https://www.wikidata.org/wiki/Q171318","display_name":"Kinship","level":2,"score":0.8751448392868042},{"id":"https://openalex.org/C112964050","wikidata":"https://www.wikidata.org/wiki/Q103459","display_name":"Livestock","level":2,"score":0.7717057466506958},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6630786061286926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6434459090232849},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6315876245498657},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5208050012588501},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46622422337532043},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4297787547111511},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41407281160354614},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4135807752609253},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.392017662525177},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34846389293670654},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.23463964462280273},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.11492812633514404},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.10510510206222534},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07793256640434265},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.07165509462356567},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivcnz51579.2020.9290558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivcnz51579.2020.9290558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W2087681821","https://openalex.org/W2096733369","https://openalex.org/W2115252128","https://openalex.org/W2127589108","https://openalex.org/W2128244002","https://openalex.org/W2161969291","https://openalex.org/W2766739066","https://openalex.org/W2791690647","https://openalex.org/W2797200251","https://openalex.org/W2964121744","https://openalex.org/W2971892976","https://openalex.org/W3080427797","https://openalex.org/W3097096317","https://openalex.org/W3099206234","https://openalex.org/W3209872747","https://openalex.org/W4293258550","https://openalex.org/W6631190155","https://openalex.org/W6677618333"],"related_works":["https://openalex.org/W1579373186","https://openalex.org/W4312685612","https://openalex.org/W2046291598","https://openalex.org/W4317827232","https://openalex.org/W2890085216","https://openalex.org/W2504703202","https://openalex.org/W4252628068","https://openalex.org/W1708418756","https://openalex.org/W2976679446","https://openalex.org/W2384651879"],"abstract_inverted_index":{"For":[0],"the":[1,8,41],"non-farmer":[2],"folk":[3],"all":[4],"sheep":[5,60],"might":[6],"look":[7],"same,":[9],"but":[10],"they":[11],"are":[12],"in":[13,34,49,53],"fact":[14],"morphologically":[15],"quite":[16],"different;":[17],"including":[18],"when":[19],"it":[20],"comes":[21],"to":[22],"facial":[23,32],"features.":[24],"Image":[25],"analysis":[26],"has":[27],"already":[28],"demonstrated":[29],"that":[30],"computer-based":[31],"recognition":[33],"livestock":[35,50],"is":[36],"very":[37],"accurate.":[38],"We":[39],"investigate":[40],"viability":[42],"of":[43,59],"deep":[44],"learning":[45],"for":[46,51,78,86],"assigning":[47],"kinship":[48,87],"use":[52],"genetic":[54,67],"evaluation-":[55],"given":[56],"two":[57,74],"images":[58],"faces,":[61],"our":[62],"proposed":[63],"model":[64],"predicts":[65],"their":[66],"relationship.":[68],"In":[69],"this":[70],"work":[71],"we":[72],"present":[73],"CNN":[75],"models:":[76],"one":[77,85],"face":[79],"detection":[80,88],"(reporting":[81,89],"80%":[82],"accuracy)":[83],"and":[84],"68%":[90],"balanced":[91],"accuracy).":[92]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}