{"id":"https://openalex.org/W2792446894","doi":"https://doi.org/10.1109/icip.2017.8296919","title":"Deep-based fisher vector for mobile visual search","display_name":"Deep-based fisher vector for mobile visual search","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2792446894","doi":"https://doi.org/10.1109/icip.2017.8296919","mag":"2792446894"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296919","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296919","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5054718310","display_name":"Chen Huang","orcid":"https://orcid.org/0000-0003-3412-3677"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Huang","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012257365","display_name":"Shengchuan Zhang","orcid":"https://orcid.org/0000-0002-0824-4945"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengchuan Zhang","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101445574","display_name":"Xianming Lin","orcid":"https://orcid.org/0000-0003-4739-8936"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianming Lin","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026771763","display_name":"Xiangrong Liu","orcid":"https://orcid.org/0000-0001-9885-1978"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangrong Liu","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016080094","display_name":"Rongrong Ji","orcid":"https://orcid.org/0000-0001-9163-2932"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongrong Ji","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21361051,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"3430","last_page":"3434"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9954000115394592,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9883999824523926,"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/computer-science","display_name":"Computer science","score":0.6767052412033081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48532170057296753},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40381157398223877},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3493805527687073}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6767052412033081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48532170057296753},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40381157398223877},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3493805527687073}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296919","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296919","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1606858007","https://openalex.org/W1966385142","https://openalex.org/W1995922888","https://openalex.org/W2012592962","https://openalex.org/W2016665365","https://openalex.org/W2069463273","https://openalex.org/W2071027807","https://openalex.org/W2099027955","https://openalex.org/W2100495367","https://openalex.org/W2108598243","https://openalex.org/W2130313186","https://openalex.org/W2144119741","https://openalex.org/W2147238549","https://openalex.org/W2148114917","https://openalex.org/W2186356322","https://openalex.org/W2500786414"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2772917594","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"We":[0,96],"tackle":[1],"the":[2,30,43,50,62,69,133,137,150],"problem":[3],"of":[4,32,45,52,72,135,160,166],"mobile":[5],"visual":[6,21],"search.":[7],"Moving":[8],"pictures":[9],"experts":[10],"group":[11],"(MPEG)":[12],"has":[13],"completed":[14],"a":[15,26,84,98,143],"standard":[16],"named":[17],"compact":[18],"descriptor":[19,48,54,65,70,122],"for":[20],"search":[22],"(CDVS)":[23],"to":[24,41,107,131,146],"provide":[25],"standardized":[27],"syntax":[28],"in":[29,115,164],"context":[31],"image":[33],"retrieval":[34,168],"application.":[35],"CDVS":[36,120,167],"applies":[37],"principal":[38],"components":[39,71],"analysis":[40],"reduce":[42,132],"dimension":[44],"local":[46,63],"feature":[47,64],"as":[49,61],"input":[51],"global":[53,121],"pipeline,":[55],"and":[56,74,82],"utilizes":[57],"traditional":[58],"fisher":[59,109],"vector":[60],"aggregation":[66],"algorithm.":[67],"However,":[68],"SIFT":[73],"Fisher":[75],"Vector":[76],"(FV)":[77],"have":[78],"highly":[79],"non-Gaussian":[80],"statistics,":[81],"applying":[83],"single":[85],"PCA":[86],"transform":[87],"can":[88],"in-fact":[89],"hurt":[90],"compression":[91],"performance":[92],"at":[93],"high":[94],"rates.":[95],"develop":[97],"net-based":[99],"architecture":[100,117,163],"combining":[101],"neural":[102],"networks":[103,130],"with":[104,119],"FV":[105,151],"layer":[106],"obtain":[108],"vector.":[110],"There":[111],"are":[112],"two":[113],"advantages":[114],"our":[116,161],"comparing":[118],"pipeline.":[123],"One":[124],"is":[125,139],"that":[126,140],"we":[127,141],"employ":[128],"\u201cautoencoder\u201d":[129],"dimensionality":[134],"data,":[136],"other":[138],"exploit":[142],"trainable":[144],"system":[145],"learn":[147],"parameters":[148],"after":[149],"codebook":[152],"obtained.":[153],"The":[154],"experiments":[155],"demonstrate":[156],"an":[157],"obvious":[158],"advantage":[159],"proposed":[162],"terms":[165],"task.":[169]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}