{"id":"https://openalex.org/W4405271933","doi":"https://doi.org/10.1109/icceic64099.2024.10775439","title":"Enhanced Cross-Modal Retrieval with Low-Rank Multi-Head Self-Attention","display_name":"Enhanced Cross-Modal Retrieval with Low-Rank Multi-Head Self-Attention","publication_year":2024,"publication_date":"2024-10-11","ids":{"openalex":"https://openalex.org/W4405271933","doi":"https://doi.org/10.1109/icceic64099.2024.10775439"},"language":"en","primary_location":{"id":"doi:10.1109/icceic64099.2024.10775439","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icceic64099.2024.10775439","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Computer Engineering and Intelligent Control (ICCEIC)","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/A5056667727","display_name":"Hancong Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hancong Liu","raw_affiliation_strings":["Beijing University of Technology,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,Beijing,China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048913613","display_name":"Jingzhong Qi","orcid":"https://orcid.org/0000-0002-4381-929X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingzhong Qi","raw_affiliation_strings":["Beijing University of Technology,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,Beijing,China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086607958","display_name":"Qing Zhu","orcid":"https://orcid.org/0000-0001-7380-485X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Zhu","raw_affiliation_strings":["Beijing University of Technology,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,Beijing,China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5056667727"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20838626,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"192","last_page":"198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.974399983882904,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.974399983882904,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9710000157356262,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9684000015258789,"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/modal","display_name":"Modal","score":0.7048186659812927},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.617081880569458},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.49893903732299805},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4585573077201843},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38564103841781616},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16989022493362427},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1193380057811737},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07690516114234924}],"concepts":[{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7048186659812927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.617081880569458},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.49893903732299805},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4585573077201843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38564103841781616},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16989022493362427},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1193380057811737},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07690516114234924},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icceic64099.2024.10775439","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icceic64099.2024.10775439","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Computer Engineering and Intelligent Control (ICCEIC)","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":29,"referenced_works":["https://openalex.org/W1905882502","https://openalex.org/W1916445035","https://openalex.org/W1957706851","https://openalex.org/W2346425926","https://openalex.org/W2778100917","https://openalex.org/W2894786240","https://openalex.org/W2956018683","https://openalex.org/W2963040148","https://openalex.org/W2963150162","https://openalex.org/W2963389687","https://openalex.org/W2963467339","https://openalex.org/W2964120214","https://openalex.org/W3035454331","https://openalex.org/W3139240072","https://openalex.org/W3159088493","https://openalex.org/W3168851777","https://openalex.org/W3173220247","https://openalex.org/W3178827611","https://openalex.org/W4220863497","https://openalex.org/W4292794825","https://openalex.org/W4303444819","https://openalex.org/W4395689368","https://openalex.org/W4401750770","https://openalex.org/W6685183736","https://openalex.org/W6735377749","https://openalex.org/W6747225742","https://openalex.org/W6762718338","https://openalex.org/W6844993126","https://openalex.org/W6848688062"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"In":[0,47],"today's":[1],"rapidly":[2],"developing":[3],"technological":[4,88,289],"innovation":[5],"environment,":[6],"cross-modal":[7,42,54,116,245],"retrieval":[8,19,55,117,177,272],"plays":[9],"a":[10,36,99,108,191,197,237,248,280],"vital":[11],"role":[12],"in":[13,119,159,263,267],"the":[14,48,115,120,152,164,169,172,180,186,219,230,233,256],"field":[15,49,121],"of":[16,27,50,84,122,168,179,215,232,240],"modern":[17],"information":[18],"and":[20,33,45,66,73,77,92,136,156,176,195,207,210,225,247,270,277,288],"data":[21,26,82,226],"analysis.":[22,124],"It":[23],"can":[24],"map":[25],"different":[28,213],"modalities":[29],"such":[30],"as":[31,129],"images":[32,76],"text":[34,78,145,154,271],"into":[35],"common":[37],"semantic":[38,102],"space,":[39],"thereby":[40],"realizing":[41],"similarity":[43],"measurement":[44],"retrieval.":[46],"patent":[51,81,123,142,160,268,286],"analysis,":[52],"image-text":[53,170],"is":[56,83],"particularly":[57],"important.":[58],"Patent":[59],"documents":[60],"usually":[61],"contain":[62],"complex":[63,153],"technical":[64],"descriptions":[65],"related":[67],"instructions.":[68],"The":[69,144,251],"ability":[70,175,221],"to":[71,113,133,149,203,222],"efficiently":[72],"accurately":[74],"retrieve":[75],"from":[79,141],"massive":[80],"great":[85],"significance":[86],"for":[87,105,284],"innovation,":[89],"competition":[90],"analysis":[91,287],"intellectual":[93],"property":[94],"protection.":[95],"This":[96],"paper":[97],"proposes":[98],"novel":[100],"visual":[101],"embedding":[103,165,193],"model":[104,126,181,257],"patents":[106],"using":[107],"low-rank":[109,199],"multi-head":[110,200],"self-attention":[111,201],"mechanism":[112,202],"improve":[114],"performance":[118],"Our":[125],"uses":[127,147],"EfficientNet":[128],"an":[130],"image":[131,269],"encoder":[132,146],"extract":[134],"richer":[135],"more":[137],"detailed":[138],"feature":[139,173],"representations":[140,214],"images.":[143],"BERT":[148],"effectively":[150],"handle":[151,223],"structure":[155],"polysemy":[157],"problems":[158],"documents.":[161],"By":[162],"optimizing":[163],"generation":[166],"process":[167],"encoder,":[171],"expression":[174],"accuracy":[178,276],"are":[182],"significantly":[183,258],"enhanced.":[184],"At":[185],"same":[187],"time,":[188],"we":[189,235],"introduced":[190],"multi-instance":[192],"network":[194],"used":[196],"new":[198],"combine":[204],"global":[205],"features":[206],"local":[208],"features,":[209],"calculated":[211],"multiple":[212,243,264],"instances,":[216],"further":[217],"improving":[218],"model's":[220],"ambiguity":[224],"diversity.":[227],"To":[228],"verify":[229],"effectiveness":[231],"model,":[234],"conducted":[236],"large":[238],"number":[239],"experiments":[241],"on":[242],"public":[244],"datasets":[246],"patent-specific":[249],"dataset.":[250],"experimental":[252],"results":[253],"show":[254],"that":[255],"outperforms":[259],"most":[260],"existing":[261],"methods":[262],"indicators,":[265],"especially":[266],"tasks,":[273],"showing":[274],"higher":[275],"robustness,":[278],"providing":[279],"strong":[281],"tool":[282],"support":[283],"future":[285],"innovation.":[290]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}