{"id":"https://openalex.org/W4416749438","doi":"https://doi.org/10.1109/iros60139.2025.11246372","title":"Deep Learning-Based Pig Behavior Captioning for Smart Livestock Farming","display_name":"Deep Learning-Based Pig Behavior Captioning for Smart Livestock Farming","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416749438","doi":"https://doi.org/10.1109/iros60139.2025.11246372"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11246372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102105301","display_name":"Honghua Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I74485261","display_name":"Shandong Agricultural University","ror":"https://ror.org/02ke8fw32","country_code":"CN","type":"education","lineage":["https://openalex.org/I74485261"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honghua Jiang","raw_affiliation_strings":["Shandong Agricultural University,College of Information Science and Engineering,Tai’an,China,271018"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Agricultural University,College of Information Science and Engineering,Tai’an,China,271018","institution_ids":["https://openalex.org/I74485261"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024930899","display_name":"Yongqing Zeng","orcid":"https://orcid.org/0000-0002-0740-2470"},"institutions":[{"id":"https://openalex.org/I74485261","display_name":"Shandong Agricultural University","ror":"https://ror.org/02ke8fw32","country_code":"CN","type":"education","lineage":["https://openalex.org/I74485261"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongqing Zeng","raw_affiliation_strings":["Shandong Agricultural University,Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology,Tai’an,China,271018"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Agricultural University,Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Technology,Tai’an,China,271018","institution_ids":["https://openalex.org/I74485261"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042431015","display_name":"Yongliang Qiao","orcid":"https://orcid.org/0000-0003-2142-0154"},"institutions":[{"id":"https://openalex.org/I2802355861","display_name":"Australian Institute of Business","ror":"https://ror.org/01wf5jq34","country_code":"AU","type":"education","lineage":["https://openalex.org/I2802355861"]},{"id":"https://openalex.org/I5681781","display_name":"The University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yongliang Qiao","raw_affiliation_strings":["The University of Adelaide,Australian Institute for Machine Learning (AIML),Adelaide,Australia,5000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Adelaide,Australian Institute for Machine Learning (AIML),Adelaide,Australia,5000","institution_ids":["https://openalex.org/I2802355861","https://openalex.org/I5681781"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1855","last_page":"1860"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.1704999953508377,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.1704999953508377,"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/T10838","display_name":"Animal Behavior and Welfare Studies","score":0.16660000383853912,"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"}},{"id":"https://openalex.org/T11214","display_name":"Human-Animal Interaction Studies","score":0.027899999171495438,"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/closed-captioning","display_name":"Closed captioning","score":0.847599983215332},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42910000681877136},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4004000127315521},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.39500001072883606},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.3774000108242035},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.375}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.847599983215332},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5360999703407288},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42910000681877136},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4004000127315521},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.39500001072883606},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.3774000108242035},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.375},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.36730000376701355},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33719998598098755},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29989999532699585},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2671999931335449},{"id":"https://openalex.org/C2988419192","wikidata":"https://www.wikidata.org/wiki/Q7155","display_name":"Animal behavior","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11246372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1895577753","https://openalex.org/W1956340063","https://openalex.org/W2101105183","https://openalex.org/W3094502228","https://openalex.org/W3157078837","https://openalex.org/W3216130706","https://openalex.org/W4206706211","https://openalex.org/W4206790550","https://openalex.org/W4283009082","https://openalex.org/W4283793362","https://openalex.org/W4289654392","https://openalex.org/W4311777769","https://openalex.org/W4313449137","https://openalex.org/W4322627364","https://openalex.org/W4380356709","https://openalex.org/W4385416242","https://openalex.org/W4385467485","https://openalex.org/W4385617829","https://openalex.org/W4387546214","https://openalex.org/W4391589924","https://openalex.org/W4407638511","https://openalex.org/W4408915053","https://openalex.org/W4410430458","https://openalex.org/W4410777497"],"related_works":[],"abstract_inverted_index":{"Precise":[0],"monitoring":[1],"of":[2,42,60,157,191],"pig":[3,61,78,106,127,170],"behavior":[4,21,107,128,171],"has":[5],"become":[6],"pivotal":[7],"for":[8,36,105,183],"enhancing":[9],"animal":[10],"welfare":[11],"and":[12,27,33,84,100,117,143,172,187],"breeding":[13],"efficiency.":[14],"However,":[15],"existing":[16],"studies":[17],"predominantly":[18],"focus":[19],"on":[20],"recognition":[22],"while":[23],"neglecting":[24],"environmental":[25,174],"influences,":[26],"lack":[28],"specialized":[29],"image":[30,50],"captioning":[31,51],"models":[32,163],"datasets":[34],"tailored":[35],"farm":[37,68],"scenarios,":[38],"hindering":[39],"textual":[40,58,108],"analysis":[41],"behavior-environment":[43,185],"interactions.":[44],"In":[45],"this":[46],"study,":[47],"a":[48,73,125,154,180],"multimodal":[49],"model":[52,71],"was":[53,134],"proposed":[54,151,177],"to":[55,76,166],"generate":[56],"semantic":[57],"descriptions":[59],"behavior,":[62],"thereby":[63],"supporting":[64],"smart":[65,196],"decision-making":[66],"in":[67,120],"management.":[69],"The":[70,145],"employs":[72],"ResNet-18":[74],"encoder":[75],"extract":[77],"visual":[79],"biometric":[80],"features":[81],"from":[82],"RGB":[83],"depth":[85],"images,":[86],"coupled":[87],"with":[88],"an":[89,93],"innovative":[90],"decoder":[91],"integrating":[92],"enhanced":[94],"Long":[95],"Short-Term":[96],"Memory":[97],"(LSTM)":[98],"network":[99],"Graph":[101],"Convolutional":[102],"Network":[103],"(GCN)":[104],"description,":[109],"effectively":[110],"resolving":[111],"the":[112,150,176,189],"input":[113],"inconsistency":[114],"between":[115],"training":[116],"inference":[118],"phases":[119],"traditional":[121],"Encoder-Decoder":[122],"architectures.":[123],"Additionally,":[124],"dedicated":[126],"dataset":[129],"comprising":[130],"9,052":[131],"annotated":[132],"images":[133],"constructed,":[135],"covering":[136],"four":[137],"behavioral":[138],"categories:":[139],"standing,":[140],"sitting,":[141],"lying,":[142],"eating.":[144],"experimental":[146],"results":[147],"show":[148],"that":[149],"approach":[152,178],"achieves":[153],"METEOR":[155],"score":[156],"88.25%,":[158],"which":[159],"is":[160],"outperformed":[161],"baseline":[162],"by":[164],"up":[165],"21.58%.":[167],"By":[168],"recognizing":[169],"interpreting":[173],"context,":[175],"introduces":[179],"practical":[181],"methodology":[182],"analyzing":[184],"interactions":[186],"facilitates":[188],"integration":[190],"LLM-embedded":[192],"robotic":[193],"systems":[194],"into":[195],"livestock":[197],"farming.":[198]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-28T00:00:00"}