{"id":"https://openalex.org/W4407466489","doi":"https://doi.org/10.1109/iccvit63928.2024.10872416","title":"Image Recognition Method Based on the Fusion of Multimodal Large Models","display_name":"Image Recognition Method Based on the Fusion of Multimodal Large Models","publication_year":2024,"publication_date":"2024-11-24","ids":{"openalex":"https://openalex.org/W4407466489","doi":"https://doi.org/10.1109/iccvit63928.2024.10872416"},"language":"en","primary_location":{"id":"doi:10.1109/iccvit63928.2024.10872416","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvit63928.2024.10872416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 2nd International Conference on Computer, Vision and Intelligent Technology (ICCVIT)","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/A5116254189","display_name":"Aiwei Zang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aiwei Zang","raw_affiliation_strings":["Nanjing Research Institute of Electronic Engineering,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Research Institute of Electronic Engineering,Nanjing,China","institution_ids":["https://openalex.org/I4210110458"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045225640","display_name":"Runxing Cao","orcid":"https://orcid.org/0000-0003-0104-9554"},"institutions":[{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renzheng Cao","raw_affiliation_strings":["Nanjing Research Institute of Electronic Engineering,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Research Institute of Electronic Engineering,Nanjing,China","institution_ids":["https://openalex.org/I4210110458"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210110458"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50493097,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.626800000667572,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.626800000667572,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.685149073600769},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5688307881355286},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5684757232666016},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4837679862976074},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44455912709236145},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44222384691238403},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3633852005004883}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.685149073600769},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5688307881355286},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5684757232666016},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4837679862976074},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44455912709236145},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44222384691238403},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3633852005004883},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccvit63928.2024.10872416","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvit63928.2024.10872416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 2nd International Conference on Computer, Vision and Intelligent Technology (ICCVIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2555160966","https://openalex.org/W2619383789","https://openalex.org/W2919115771","https://openalex.org/W3212266429"],"related_works":["https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2139242969","https://openalex.org/W2284201331","https://openalex.org/W2095903272","https://openalex.org/W1989561795"],"abstract_inverted_index":{"With":[0],"the":[1,17,55,66,71,88],"development":[2],"of":[3,19,70],"deep":[4,33,82],"learning":[5,34],"technology,":[6],"image":[7,43,85],"recognition":[8,20,44,86],"has":[9],"made":[10],"significant":[11],"progress":[12],"in":[13,28,73],"various":[14],"fields.":[15],"However,":[16],"performance":[18],"models":[21],"is":[22],"limited":[23],"by":[24],"single-modal":[25,84],"information,":[26],"especially":[27],"complex":[29],"scenarios":[30],"where":[31],"traditional":[32,81],"methods":[35],"lack":[36],"generalization":[37],"ability.":[38],"This":[39],"paper":[40],"proposes":[41],"an":[42],"method":[45,90],"based":[46],"on":[47,93],"multimodal":[48,58],"large":[49],"model":[50,72],"fusion":[51],"(BFMLM),":[52],"which":[53],"leverages":[54],"correlation":[56],"between":[57],"data":[59],"to":[60,80],"achieve":[61],"cross-modal":[62],"feature":[63],"fusion,":[64],"improving":[65],"accuracy":[67],"and":[68],"robustness":[69],"target":[74],"recognition.":[75],"Experiments":[76],"show":[77],"that,":[78],"compared":[79],"learning-based":[83],"algorithms,":[87],"proposed":[89],"performs":[91],"better":[92],"multiple":[94],"datasets.":[95]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
