{"id":"https://openalex.org/W2656941364","doi":"https://doi.org/10.1109/icassp.2017.7952691","title":"Cross-modality matching based on Fisher Vector with neural word embeddings and deep image features","display_name":"Cross-modality matching based on Fisher Vector with neural word embeddings and deep image features","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2656941364","doi":"https://doi.org/10.1109/icassp.2017.7952691","mag":"2656941364"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2017.7952691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7952691","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 Acoustics, Speech and Signal Processing (ICASSP)","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/A5100733758","display_name":"Liang Han","orcid":"https://orcid.org/0000-0002-6148-1114"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Han","raw_affiliation_strings":["School of Electronic and Computer Engineering, Peking University, Nanshan District, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University, Nanshan District, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017052768","display_name":"Wenmin Wang","orcid":"https://orcid.org/0000-0003-2664-4413"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenmin Wang","raw_affiliation_strings":["School of Electronic and Computer Engineering, Peking University, Nanshan District, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University, Nanshan District, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032782101","display_name":"Mengdi Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengdi Fan","raw_affiliation_strings":["School of Electronic and Computer Engineering, Peking University, Nanshan District, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University, Nanshan District, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060843253","display_name":"Ronggang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronggang Wang","raw_affiliation_strings":["School of Electronic and Computer Engineering, Peking University, Nanshan District, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University, Nanshan District, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"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":null,"issue":null,"first_page":"2921","last_page":"2925"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T11714","display_name":"Multimodal Machine Learning Applications","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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8037381172180176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7495168447494507},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6921945214271545},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.612403392791748},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.5750264525413513},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5644155144691467},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5194096565246582},{"id":"https://openalex.org/keywords/fisher-kernel","display_name":"Fisher kernel","score":0.501593828201294},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4970422089099884},{"id":"https://openalex.org/keywords/semantic-matching","display_name":"Semantic matching","score":0.48686614632606506},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.466171532869339},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.4498540163040161},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.4459713101387024},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.3545609712600708},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24174997210502625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1165648102760315},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.08906027674674988}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8037381172180176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7495168447494507},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6921945214271545},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.612403392791748},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.5750264525413513},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5644155144691467},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5194096565246582},{"id":"https://openalex.org/C207798031","wikidata":"https://www.wikidata.org/wiki/Q8563425","display_name":"Fisher kernel","level":5,"score":0.501593828201294},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4970422089099884},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.48686614632606506},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.466171532869339},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.4498540163040161},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4459713101387024},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3545609712600708},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24174997210502625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1165648102760315},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.08906027674674988},{"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2017.7952691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7952691","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 Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W93016980","https://openalex.org/W1614298861","https://openalex.org/W1686810756","https://openalex.org/W1880262756","https://openalex.org/W1957706851","https://openalex.org/W2012011657","https://openalex.org/W2035650150","https://openalex.org/W2042060255","https://openalex.org/W2071207147","https://openalex.org/W2106277773","https://openalex.org/W2119775030","https://openalex.org/W2137434377","https://openalex.org/W2138118304","https://openalex.org/W2147238549","https://openalex.org/W2151103935","https://openalex.org/W2155541015","https://openalex.org/W2155797815","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2164530430","https://openalex.org/W2326180695","https://openalex.org/W2465870074","https://openalex.org/W4294375521","https://openalex.org/W6636510571","https://openalex.org/W6637373629","https://openalex.org/W6639619044","https://openalex.org/W6677994088","https://openalex.org/W6680347996","https://openalex.org/W6682778277","https://openalex.org/W6683120131","https://openalex.org/W6683411478","https://openalex.org/W6684191040","https://openalex.org/W6719475499"],"related_works":["https://openalex.org/W2063218608","https://openalex.org/W4386105885","https://openalex.org/W2184288218","https://openalex.org/W2947282851","https://openalex.org/W2374066281","https://openalex.org/W4387423606","https://openalex.org/W2071180033","https://openalex.org/W2036058638","https://openalex.org/W2528082075","https://openalex.org/W155590726"],"abstract_inverted_index":{"Cross-modal":[0],"retrieval,":[1],"which":[2],"aims":[3],"to":[4],"solve":[5],"the":[6,9,12,25,28,37,72,96],"problem":[7],"that":[8],"query":[10],"and":[11,21,45,54,65,91,98,103],"retrieved":[13],"results":[14],"are":[15,61],"from":[16],"different":[17],"modality,":[18],"becomes":[19],"more":[20,22],"essential":[23],"with":[24,57],"development":[26],"of":[27,39,43],"Internet.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33,78],"mainly":[34],"focus":[35],"on":[36,89],"exploration":[38],"high-level":[40],"semantic":[41,84],"representation":[42],"image":[44,52],"text":[46],"for":[47,83,100],"cross-modal":[48],"matching.":[49],"Deep":[50],"convolutional":[51],"features":[53,67],"Fisher":[55],"Vector":[56],"neural":[58],"word":[59],"embeddings":[60],"utilized":[62],"as":[63],"visual":[64],"textual":[66],"respectively.":[68],"To":[69],"further":[70],"investigate":[71],"correlation":[73],"among":[74],"heterogeneous":[75],"multimodal":[76],"characteristics,":[77],"use":[79],"multiclass":[80],"logistic":[81],"classifier":[82],"matching":[85],"across":[86],"modalities.":[87],"Experiments":[88],"Wikipedia":[90],"Pascal":[92],"Sentence":[93],"dataset":[94],"demonstrate":[95],"robustness":[97],"effectiveness":[99],"both":[101],"Img2Text":[102],"Text2Img":[104],"retrieval":[105],"tasks.":[106]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
