{"id":"https://openalex.org/W4390204427","doi":"https://doi.org/10.1109/access.2023.3346970","title":"RGB-D Visual Saliency Detection Algorithm Based on Information Guided and Multimodal Feature Fusion","display_name":"RGB-D Visual Saliency Detection Algorithm Based on Information Guided and Multimodal Feature Fusion","publication_year":2023,"publication_date":"2023-12-25","ids":{"openalex":"https://openalex.org/W4390204427","doi":"https://doi.org/10.1109/access.2023.3346970"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3346970","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3346970","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10373856.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10373856.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090281757","display_name":"Lijuan Xu","orcid":"https://orcid.org/0000-0003-0377-6659"},"institutions":[{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]},{"id":"https://openalex.org/I4400573295","display_name":"Guangzhou Huashang College","ror":"https://ror.org/0546x0d08","country_code":null,"type":"education","lineage":["https://openalex.org/I4400573295"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijuan Xu","raw_affiliation_strings":["School of Data Science, Guangzhou Huashang College, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science, Guangzhou Huashang College, Guangzhou, China","institution_ids":["https://openalex.org/I4210113138","https://openalex.org/I4400573295"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xuemiao Xu","orcid":"https://orcid.org/0009-0008-4172-0019"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuemiao Xu","raw_affiliation_strings":["School of Future Technology, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0008-4172-0019","affiliations":[{"raw_affiliation_string":"School of Future Technology, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.8509,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.7606902,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"268","last_page":"280"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9997000098228455,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9997000098228455,"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/T12496","display_name":"Color perception and design","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14254","display_name":"Digital Media and Visual Art","score":0.9674000144004822,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/computer-science","display_name":"Computer science","score":0.7552416324615479},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.671294629573822},{"id":"https://openalex.org/keywords/information-fusion","display_name":"Information fusion","score":0.6159278750419617},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5926191806793213},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5675661563873291},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5602993965148926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5083698630332947},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5030331015586853},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.48532360792160034},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4543752372264862},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.43570947647094727},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.422435998916626},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1446593999862671}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7552416324615479},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.671294629573822},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.6159278750419617},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5926191806793213},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5675661563873291},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5602993965148926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5083698630332947},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5030331015586853},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.48532360792160034},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4543752372264862},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.43570947647094727},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.422435998916626},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1446593999862671},{"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":2,"locations":[{"id":"doi:10.1109/access.2023.3346970","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3346970","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10373856.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5b40ba15d59949c98a0e2dac055c423c","is_oa":true,"landing_page_url":"https://doaj.org/article/5b40ba15d59949c98a0e2dac055c423c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 268-280 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3346970","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3346970","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10373856.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G220378590","display_name":null,"funder_award_id":"2019KTSCX236","funder_id":"https://openalex.org/F4320328712","funder_display_name":"Guangdong Ordinary University"}],"funders":[{"id":"https://openalex.org/F4320328712","display_name":"Guangdong Ordinary University","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390204427.pdf","grobid_xml":"https://content.openalex.org/works/W4390204427.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W2059270233","https://openalex.org/W3116926628","https://openalex.org/W3126725132","https://openalex.org/W3164802490","https://openalex.org/W3202061712","https://openalex.org/W3212645988","https://openalex.org/W4205646066","https://openalex.org/W4205971281","https://openalex.org/W4213137273","https://openalex.org/W4281710415","https://openalex.org/W4285242672","https://openalex.org/W4288685423","https://openalex.org/W4294840771","https://openalex.org/W4304694724","https://openalex.org/W4308945382","https://openalex.org/W4311972917","https://openalex.org/W4312612915","https://openalex.org/W4318832835","https://openalex.org/W4320887289","https://openalex.org/W4321498173","https://openalex.org/W4381430461"],"related_works":["https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3214791684","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2370195708","https://openalex.org/W1490651872"],"abstract_inverted_index":{"With":[0],"the":[1,8,31,76,126,141,145,168,173,177,183,216],"development":[2],"of":[3,10,21,33,46,79,128,144,167,182],"scientific":[4],"information":[5,22,35,111,138],"technology":[6],"and":[7,14,24,88,113,117,131,156,160,188,219,232,238],"popularization":[9],"electronic":[11],"devices,":[12],"images":[13],"videos":[15],"have":[16],"become":[17,41],"very":[18,43],"important":[19,44],"forms":[20],"expression":[23],"carriers":[25],"in":[26,67,71,96,172,221,224],"our":[27],"current":[28,47,72],"lives.":[29],"Accelerating":[30],"mining":[32,78],"valuable":[34],"content":[36],"from":[37,86,149],"massive":[38],"data":[39,80],"has":[40],"a":[42,222],"aspect":[45],"computer":[48,68],"vision":[49],"research.":[50],"The":[51,164,196,205],"saliency":[52,133],"object":[53,218],"detection":[54,106,207],"method,":[55],"which":[56,212],"is":[57,63,83,90,108,122,147,213],"related":[58],"to":[59,124],"human":[60],"visual":[61],"attention,":[62],"gradually":[64],"being":[65],"applied":[66],"processing.":[69],"However,":[70],"color":[73,104],"depth":[74,81,105],"models,":[75,159],"association":[77],"clues":[82],"still":[84,91],"far":[85],"sufficient,":[87],"there":[89],"significant":[92],"room":[93],"for":[94,110,234],"improvement":[95,180],"image":[97],"quality.":[98],"Based":[99],"on":[100,198],"this,":[101],"an":[102,118],"improved":[103],"model":[107,121,170,185],"proposed":[109,171],"guided":[112],"multi":[114,157],"feature":[115,137,153],"fusion,":[116],"absorption":[119],"Markov":[120],"introduced":[123],"optimize":[125],"guidance":[127,143],"low-level,":[129],"middle-level,":[130],"high-level":[132],"maps,":[134],"grasping":[135],"different":[136],"contents.":[139],"Subsequently,":[140],"gradual":[142],"network":[146],"achieved":[148],"aspects":[150],"such":[151],"as":[152],"encoding,":[154],"multi-scale":[155],"attention":[158,161],"refinement":[162],"mechanisms.":[163],"experimental":[165],"analysis":[166],"fusion":[169,184],"study":[174],"showed":[175],"that":[176],"average":[178],"classification":[179],"accuracy":[181],"reached":[186],"5.23%,":[187],"its":[189],"error":[190],"value":[191,231],"was":[192],"less":[193],"than":[194],"0.1.":[195],"effectiveness":[197],"all":[199],"four":[200],"quantitative":[201],"indicators":[202],"exceeded":[203,210],"92%.":[204],"system\u2019s":[206],"response":[208],"rate":[209],"93%,":[211],"limited":[214],"by":[215],"target":[217,235],"results":[220],"decrease":[223],"accuracy.":[225],"This":[226],"algorithm":[227],"can":[228],"provide":[229],"reference":[230],"means":[233],"localization":[236],"recognition":[237],"virtual":[239],"scene":[240],"detection.":[241]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}