{"id":"https://openalex.org/W4415399137","doi":"https://doi.org/10.1109/spml66318.2025.11199799","title":"Research on Multi-View Cattle Facial Recognition Algorithm Based on Feature Matching","display_name":"Research on Multi-View Cattle Facial Recognition Algorithm Based on Feature Matching","publication_year":2025,"publication_date":"2025-07-15","ids":{"openalex":"https://openalex.org/W4415399137","doi":"https://doi.org/10.1109/spml66318.2025.11199799"},"language":null,"primary_location":{"id":"doi:10.1109/spml66318.2025.11199799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spml66318.2025.11199799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 8th International Conference on Signal Processing and Machine Learning (SPML)","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/A5100346729","display_name":"Zhiqiang Zheng","orcid":"https://orcid.org/0000-0003-2656-6689"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Zheng","raw_affiliation_strings":["College of Electronic Information Engineering, Inner Mongolia University,Hohhot,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Information Engineering, Inner Mongolia University,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100683070","display_name":"Bo Wen","orcid":"https://orcid.org/0000-0003-2287-473X"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Wen","raw_affiliation_strings":["College of Electronic Information Engineering, Inner Mongolia University,Hohhot,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Information Engineering, Inner Mongolia University,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025918703","display_name":"Zhi Weng","orcid":"https://orcid.org/0000-0001-8102-6875"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Weng","raw_affiliation_strings":["College of Electronic Information Engineering, Inner Mongolia University,Hohhot,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Information Engineering, Inner Mongolia University,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25260394,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.1046999990940094,"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":0.1046999990940094,"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/T13027","display_name":"Applied Advanced Technologies","score":0.07569999992847443,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.04340000078082085,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6794000267982483},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5629000067710876},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5336999893188477},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4771000146865845},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4546000063419342},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4162999987602234},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.36649999022483826},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.350600004196167}],"concepts":[{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6794000267982483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6592000126838684},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5834000110626221},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5629000067710876},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5336999893188477},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4771000146865845},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4546000063419342},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4162999987602234},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.350600004196167},{"id":"https://openalex.org/C61455927","wikidata":"https://www.wikidata.org/wiki/Q1030529","display_name":"Blossom algorithm","level":3,"score":0.3416000008583069},{"id":"https://openalex.org/C2780505807","wikidata":"https://www.wikidata.org/wiki/Q1208989","display_name":"Beef cattle","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C158096908","wikidata":"https://www.wikidata.org/wiki/Q3983303","display_name":"Template matching","level":3,"score":0.31459999084472656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2989000082015991},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28529998660087585},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.26510000228881836},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.26420000195503235},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2590000033378601}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spml66318.2025.11199799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spml66318.2025.11199799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 8th International Conference on Signal Processing and Machine Learning (SPML)","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,59,123],"recent":[1],"years,":[2],"with":[3,90,154],"the":[4,11,27,49,67,84,91,102,106,114,124,128,134,139,143,168,173],"advancement":[5],"of":[6,10,29,51,116,149,157],"transformation":[7],"and":[8,16,56,77,111,133,152,164],"upgrading":[9],"animal":[12,31],"husbandry":[13],"industry,":[14],"intelligent":[15,43],"precise":[17],"breeding":[18],"technology":[19],"has":[20],"gradually":[21],"become":[22],"an":[23],"important":[24],"direction":[25],"for":[26,183],"development":[28],"modern":[30],"husbandry.":[32],"Among":[33],"them,":[34],"cattle":[35,65,74,80,118],"individual":[36,117],"identification,":[37],"as":[38,66],"a":[39,72,79],"key":[40],"link":[41],"in":[42,48,147,170,185],"farming,":[44],"is":[45,176],"widely":[46],"used":[47],"fields":[50],"health":[52],"monitoring,":[53],"reproduction":[54],"management":[55],"behavioural":[57],"research.":[58],"this":[60],"paper,":[61],"taking":[62],"Simmental":[63],"beef":[64],"research":[68],"object,":[69],"we":[70],"constructed":[71],"multi-viewpoint":[73],"facial":[75],"dataset":[76,132],"proposed":[78,140],"identification":[81],"method":[82,141],"combining":[83],"descriptor-enhanced":[85],"SuperPoint-Booster":[86],"feature":[87,94,107],"extraction":[88],"network":[89],"improved":[92],"SuperGlue":[93],"matching":[95,109,150,171],"model.":[96],"The":[97],"experimental":[98],"results":[99],"show":[100],"that":[101],"model":[103],"significantly":[104,177],"improves":[105],"point":[108],"accuracy":[110,115,151],"substantially":[112],"increases":[113],"recognition":[119,155],"under":[120],"different":[121],"angles.":[122],"tests":[125],"on":[126],"both":[127],"small":[129],"viewpoint":[130,136],"variations":[131,137],"large":[135],"dataset,":[138],"outperforms":[142],"traditional":[144],"algorithm":[145],"combinations":[146],"terms":[148],"robustness,":[153],"accuracies":[156],"<tex":[158],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[159],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">${9":[160],"4.":[161],"7":[162],"\\%}$</tex>":[163],"79.5%,":[165],"respectively.":[166],"Despite":[167],"increase":[169],"time,":[172],"overall":[174],"performance":[175],"improved,":[178],"demonstrating":[179],"its":[180],"vast":[181],"potential":[182],"use":[184],"real-world":[186],"ranch":[187],"management.":[188]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-22T00:00:00"}