{"id":"https://openalex.org/W4388893782","doi":"https://doi.org/10.1109/tencon58879.2023.10322403","title":"Comparing Deep Learning Object detection Methods for Real Time Cow Detection","display_name":"Comparing Deep Learning Object detection Methods for Real Time Cow Detection","publication_year":2023,"publication_date":"2023-10-31","ids":{"openalex":"https://openalex.org/W4388893782","doi":"https://doi.org/10.1109/tencon58879.2023.10322403"},"language":"en","primary_location":{"id":"doi:10.1109/tencon58879.2023.10322403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon58879.2023.10322403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2023 - 2023 IEEE Region 10 Conference (TENCON)","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/A5093314590","display_name":"Gichuki Wambui Martha","orcid":null},"institutions":[{"id":"https://openalex.org/I26805570","display_name":"Jomo Kenyatta University of Agriculture and Technology","ror":"https://ror.org/015h5sy57","country_code":"KE","type":"education","lineage":["https://openalex.org/I26805570"]}],"countries":["KE"],"is_corresponding":false,"raw_author_name":"Gichuki Wambui Martha","raw_affiliation_strings":["Jomo Kenyatta University of Agriculture & Technology,Computing Department: School of Computing & Information Technology,Nairobi,Kenya"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jomo Kenyatta University of Agriculture & Technology,Computing Department: School of Computing & Information Technology,Nairobi,Kenya","institution_ids":["https://openalex.org/I26805570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109939947","display_name":"Ronald Waweru Mwangi","orcid":null},"institutions":[{"id":"https://openalex.org/I26805570","display_name":"Jomo Kenyatta University of Agriculture and Technology","ror":"https://ror.org/015h5sy57","country_code":"KE","type":"education","lineage":["https://openalex.org/I26805570"]}],"countries":["KE"],"is_corresponding":false,"raw_author_name":"Ronald Waweru Mwangi","raw_affiliation_strings":["Jomo Kenyatta University of Agriculture & Technology,Computing Department: School of Computing & Information Technology,Nairobi,Kenya"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jomo Kenyatta University of Agriculture & Technology,Computing Department: School of Computing & Information Technology,Nairobi,Kenya","institution_ids":["https://openalex.org/I26805570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069698375","display_name":"Supavadee Aramvith","orcid":"https://orcid.org/0000-0001-9840-3171"},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Supavadee Aramvith","raw_affiliation_strings":["Chulalongkorn University,Department of Electrical Engineering: Faculty of Engineering,Bangkok,Thailand","Department of Electrical Engineering: Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chulalongkorn University,Department of Electrical Engineering: Faculty of Engineering,Bangkok,Thailand","institution_ids":["https://openalex.org/I158708052"]},{"raw_affiliation_string":"Department of Electrical Engineering: Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051388166","display_name":"Richard Rimiru","orcid":"https://orcid.org/0000-0003-3190-1007"},"institutions":[{"id":"https://openalex.org/I26805570","display_name":"Jomo Kenyatta University of Agriculture and Technology","ror":"https://ror.org/015h5sy57","country_code":"KE","type":"education","lineage":["https://openalex.org/I26805570"]}],"countries":["KE"],"is_corresponding":false,"raw_author_name":"Richard Rimiru","raw_affiliation_strings":["Jomo Kenyatta University of Agriculture & Technology,Computing Department: School of Computing & Information Technology,Nairobi,Kenya"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jomo Kenyatta University of Agriculture & Technology,Computing Department: School of Computing & Information Technology,Nairobi,Kenya","institution_ids":["https://openalex.org/I26805570"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9282,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.76768772,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1187","last_page":"1192"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12486","display_name":"Food Supply Chain Traceability","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12486","display_name":"Food Supply Chain Traceability","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10838","display_name":"Animal Behavior and Welfare Studies","score":0.9757999777793884,"subfield":{"id":"https://openalex.org/subfields/3404","display_name":"Small Animals"},"field":{"id":"https://openalex.org/fields/34","display_name":"Veterinary"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8075398206710815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7823867797851562},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7807550430297852},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7533886432647705},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6992289423942566},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5322691202163696},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5048864483833313},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4870913028717041},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4483177661895752},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.43977412581443787},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3530207872390747}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8075398206710815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7823867797851562},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7807550430297852},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7533886432647705},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6992289423942566},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5322691202163696},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5048864483833313},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4870913028717041},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4483177661895752},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.43977412581443787},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3530207872390747},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon58879.2023.10322403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon58879.2023.10322403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2023 - 2023 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2570343428","https://openalex.org/W2764259953","https://openalex.org/W2892389796","https://openalex.org/W2963037989","https://openalex.org/W2988916019","https://openalex.org/W3033835801","https://openalex.org/W3091519774","https://openalex.org/W3135016280","https://openalex.org/W3146332956","https://openalex.org/W3163996247","https://openalex.org/W4205900964","https://openalex.org/W4207057737","https://openalex.org/W4220795602","https://openalex.org/W4288055089","https://openalex.org/W4291819654","https://openalex.org/W4293584584","https://openalex.org/W4297676427","https://openalex.org/W4319600834","https://openalex.org/W4366422633","https://openalex.org/W4385800646","https://openalex.org/W4386076325","https://openalex.org/W6750227808","https://openalex.org/W6841403513","https://openalex.org/W6843239693"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2949096641","https://openalex.org/W2970686063"],"abstract_inverted_index":{"Deep":[0],"learning":[1,73,202],"algorithms":[2,21],"particularly":[3],"Convolutional":[4],"Neural":[5],"Networks":[6],"(CNNs)":[7],"are":[8,45],"the":[9,125,133,146,169,187,192,197],"state-of-the-art":[10],"techniques":[11],"for":[12,204],"object":[13,74,90],"detection,":[14,206],"classification,":[15],"segmentation":[16],"and":[17,49,80,118,131,154,158,195],"behaviour":[18],"classification.":[19],"These":[20],"have":[22],"extensive":[23],"application":[24],"across":[25],"various":[26],"domains":[27],"including":[28],"agriculture.":[29],"However,":[30],"cow":[31,95,110,138,205],"identification":[32],"in":[33,89,127,186,208],"dairy":[34,103],"farming":[35],"still":[36],"relies":[37],"on":[38,86],"methods":[39],"like":[40],"direct":[41],"visual":[42],"monitoring":[43],"which":[44,60,82],"time":[46],"consuming,":[47],"costly":[48],"inaccurate;":[50],"or":[51,66],"use":[52],"of":[53,145,152,177,191,200],"invasive":[54],"contact":[55],"devices":[56],"such":[57],"as":[58],"sensors":[59],"can":[61],"cause":[62],"discomfort":[63],"during":[64],"attachment":[65],"removal.":[67],"This":[68,180],"research":[69,181,189],"compared":[70],"three":[71,134],"deep":[72,201],"detection":[75,91],"models":[76,135,203],"i.e.":[77],"YOLOv5,":[78],"YOLOv7":[79],"YOLOv8,":[81],"were":[83],"selected":[84],"based":[85],"their":[87],"performance":[88],"tasks.":[92],"We":[93],"generated":[94],"images":[96,126],"from":[97,100],"videos":[98],"captured":[99],"a":[101,174,183],"housed":[102],"cattle":[104],"barn.":[105],"The":[106],"dataset":[107],"had":[108],"11,828":[109],"images,":[111],"augmented":[112],"to":[113,136],"depict":[114],"different":[115],"illumination":[116],"conditions":[117],"using":[119,168],"makesense":[120],"AI":[121],"tool,":[122],"we":[123],"annotated":[124],"YOLO":[128,193],"format,":[129],"trained":[130],"validated":[132],"visualize":[137],"bounding":[139],"boxes.":[140],"Our":[141],"approach":[142],"demonstrates":[143],"efficiency":[144],"YOLOv8":[147,163],"model,":[148],"achieving":[149,173],"an":[150],"accuracy":[151],"94.7%":[153],"93":[155],"%":[156],"before":[157],"after":[159],"data":[160],"augmentation":[161],"respectively.":[162],"baseline":[164],"model":[165],"was":[166],"finetuned":[167],"Ray":[170],"Tune":[171],"library":[172],"mAP@O.50":[175],"score":[176],"92.":[178],"9%.":[179],"makes":[182],"significant":[184],"contribution":[185],"future":[188],"direction":[190],"algorithm":[194],"highlights":[196],"practical":[198],"implementation":[199],"applicable":[207],"livestock":[209],"management.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}