{"id":"https://openalex.org/W2588277946","doi":"https://doi.org/10.1109/cisp-bmei.2016.7852741","title":"An improved feature fusion algorithm for image retrieval","display_name":"An improved feature fusion algorithm for image retrieval","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2588277946","doi":"https://doi.org/10.1109/cisp-bmei.2016.7852741","mag":"2588277946"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2016.7852741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2016.7852741","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5048663011","display_name":"Shilin Che","orcid":null},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilin Che","raw_affiliation_strings":["College of Computer Science and Technology, Wuhan University of Science and Technology","Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Wuhan University of Science and Technology","institution_ids":["https://openalex.org/I43922553"]},{"raw_affiliation_string":"Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial, Wuhan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043765354","display_name":"Dongfang Chen","orcid":"https://orcid.org/0009-0006-3751-7400"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongfang Chen","raw_affiliation_strings":["College of Computer Science and Technology, Wuhan University of Science and Technology","Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Wuhan University of Science and Technology","institution_ids":["https://openalex.org/I43922553"]},{"raw_affiliation_string":"Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial, Wuhan, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109834190","display_name":"Xiaofeng Wang","orcid":"https://orcid.org/0000-0001-6259-7971"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofeng Wang","raw_affiliation_strings":["College of Computer Science and Technology, Wuhan University of Science and Technology","Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Wuhan University of Science and Technology","institution_ids":["https://openalex.org/I43922553"]},{"raw_affiliation_string":"Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial, Wuhan, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I43922553"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"39","issue":null,"first_page":"384","last_page":"389"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994999766349792,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994999766349792,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9983000159263611,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9710999727249146,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7920185923576355},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7019565105438232},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6694382429122925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6605764031410217},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6304476261138916},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5510186553001404},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5468371510505676},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.4853771924972534},{"id":"https://openalex.org/keywords/feature-detection","display_name":"Feature detection (computer vision)","score":0.48516756296157837},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47878921031951904},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.47730696201324463},{"id":"https://openalex.org/keywords/bag-of-words-model-in-computer-vision","display_name":"Bag-of-words model in computer vision","score":0.4653521180152893},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.41601866483688354},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3600938320159912},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.1777838170528412}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7920185923576355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7019565105438232},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6694382429122925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6605764031410217},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6304476261138916},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5510186553001404},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5468371510505676},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.4853771924972534},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.48516756296157837},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47878921031951904},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.47730696201324463},{"id":"https://openalex.org/C167611913","wikidata":"https://www.wikidata.org/wiki/Q6884747","display_name":"Bag-of-words model in computer vision","level":5,"score":0.4653521180152893},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.41601866483688354},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3600938320159912},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.1777838170528412},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"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/cisp-bmei.2016.7852741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2016.7852741","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1554018745","https://openalex.org/W1677409904","https://openalex.org/W1967643748","https://openalex.org/W1979931042","https://openalex.org/W1991084032","https://openalex.org/W2065296697","https://openalex.org/W2076188996","https://openalex.org/W2135364649","https://openalex.org/W2151103935","https://openalex.org/W2157573324","https://openalex.org/W2331698647","https://openalex.org/W2362170930","https://openalex.org/W2380323950","https://openalex.org/W2384012972"],"related_works":["https://openalex.org/W2158102958","https://openalex.org/W2391745328","https://openalex.org/W4214649316","https://openalex.org/W2095903272","https://openalex.org/W2887520098","https://openalex.org/W2554790198","https://openalex.org/W1995462736","https://openalex.org/W2938717424","https://openalex.org/W2028757524","https://openalex.org/W2499029474"],"abstract_inverted_index":{"Single":[0],"feature":[1,43,55,85,91,94],"extract":[2],"method":[3,21,65,104,135,146,162,186,202],"for":[4,154,203],"image":[5,24,28,32,200,206],"retrieval":[6,190,201],"usually":[7,30],"cannot":[8],"get":[9],"good":[10],"results":[11,181],"and":[12,73,92,99,113,117,170,192],"it":[13,196],"is":[14,49,86,109,136,147,197],"hard":[15],"to":[16,76,105,122,138,149],"find":[17,77,174,195],"a":[18,188,198],"stable":[19,199],"fusion":[20,44,56],"when":[22],"across":[23],"datasets":[25],"because":[26],"the":[27,71,78,89,96,124,140,151,155,158,164,180],"descriptors":[29],"describe":[31],"from":[33],"single":[34],"aspect.":[35],"For":[36],"this":[37,52,64,82,184],"pragmatic":[38],"issue,":[39],"an":[40,110,132],"improved":[41],"FCTH-BoVW":[42,48],"algorithm":[45],"called":[46],"robust":[47],"proposed":[50,137],"in":[51,120],"paper.":[53],"Traditional":[54],"methods":[57],"almost":[58],"use":[59,100],"liner":[60],"weight":[61,134],"method,":[62],"but":[63],"will":[66],"be":[67],"easily":[68],"affected":[69],"by":[70],"weights,":[72],"not":[74],"easy":[75],"optimal":[79],"weights.":[80],"In":[81],"paper,":[83],"FCTH":[84,108],"used":[87],"as":[88,95,127],"global":[90,141,169],"BoVW":[93],"local":[97,159,171],"feature,":[98],"k-reciprocal":[101],"nearest":[102],"neighbors":[103],"fuse":[106],"them.":[107],"efficient":[111],"descriptor":[112],"contains":[114],"both":[115,168],"color":[116],"texture":[118],"information,":[119],"order":[121],"emphasize":[123],"center":[125],"area":[126],"main":[128],"region":[129],"of":[130,157,167,205],"interest,":[131],"annular":[133],"improve":[139],"feature.":[142,160],"A":[143],"soft":[144],"assignment":[145],"adopted":[148],"quantize":[150],"visual":[152],"words":[153],"improvement":[156],"This":[161],"enhances":[163],"description":[165],"ability":[166],"features.":[172],"We":[173],"those":[175],"improvements":[176],"are":[177],"quite":[178],"practical,":[179],"show":[182],"that":[183],"fused":[185],"gets":[187],"higher":[189],"precision,":[191],"we":[193],"also":[194],"varieties":[204],"datasets.":[207]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}