{"id":"https://openalex.org/W2790730828","doi":"https://doi.org/10.1109/ipta.2017.8310096","title":"Enlarging the discriminability of bag-of-words representations with deep convolutional features","display_name":"Enlarging the discriminability of bag-of-words representations with deep convolutional features","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2790730828","doi":"https://doi.org/10.1109/ipta.2017.8310096","mag":"2790730828"},"language":"en","primary_location":{"id":"doi:10.1109/ipta.2017.8310096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta.2017.8310096","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://publica.fraunhofer.de/documents/N-487365.html","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085315644","display_name":"Daniel Manger","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Daniel Manger","raw_affiliation_strings":["Fraunhofer IOSB, Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IOSB, Karlsruhe, Germany","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055413916","display_name":"Dieter Willersinn","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dieter Willersinn","raw_affiliation_strings":["Fraunhofer IOSB, Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IOSB, Karlsruhe, Germany","institution_ids":["https://openalex.org/I4210111500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5085315644"],"corresponding_institution_ids":["https://openalex.org/I4210111500"],"apc_list":null,"apc_paid":null,"fwci":0.1849,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.60629428,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.9990000128746033,"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":0.9957000017166138,"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":0.7793756723403931},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.7064236402511597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7062013149261475},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.6917048096656799},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6761182546615601},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6508424878120422},{"id":"https://openalex.org/keywords/bag-of-words-model-in-computer-vision","display_name":"Bag-of-words model in computer vision","score":0.5641055107116699},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.561185896396637},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.5538288354873657},{"id":"https://openalex.org/keywords/bag-of-words-model","display_name":"Bag-of-words model","score":0.495837539434433},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4908462166786194},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.45971205830574036},{"id":"https://openalex.org/keywords/codebook","display_name":"Codebook","score":0.44706207513809204},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42401203513145447},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2808946371078491}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7793756723403931},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.7064236402511597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7062013149261475},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.6917048096656799},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6761182546615601},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6508424878120422},{"id":"https://openalex.org/C167611913","wikidata":"https://www.wikidata.org/wiki/Q6884747","display_name":"Bag-of-words model in computer vision","level":5,"score":0.5641055107116699},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.561185896396637},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.5538288354873657},{"id":"https://openalex.org/C13672336","wikidata":"https://www.wikidata.org/wiki/Q3460803","display_name":"Bag-of-words model","level":2,"score":0.495837539434433},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4908462166786194},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.45971205830574036},{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.44706207513809204},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42401203513145447},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2808946371078491}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ipta.2017.8310096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta.2017.8310096","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA)","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-487365","is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-487365.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IOSB","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/400009","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/400009","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":{"id":"pmh:oai:fraunhofer.de:N-487365","is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-487365.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IOSB","raw_type":"Conference Paper"},"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G352791218","display_name":null,"funder_award_id":"(BMBF)","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G7225624288","display_name":null,"funder_award_id":"This work was","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"}],"funders":[{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W204268067","https://openalex.org/W1524680991","https://openalex.org/W1556531089","https://openalex.org/W1686810756","https://openalex.org/W1972378554","https://openalex.org/W1979931042","https://openalex.org/W2003340926","https://openalex.org/W2012592962","https://openalex.org/W2023991840","https://openalex.org/W2027252237","https://openalex.org/W2031332477","https://openalex.org/W2058948131","https://openalex.org/W2062118960","https://openalex.org/W2065296697","https://openalex.org/W2066477856","https://openalex.org/W2081332440","https://openalex.org/W2100398441","https://openalex.org/W2122934855","https://openalex.org/W2130230179","https://openalex.org/W2131846894","https://openalex.org/W2141362318","https://openalex.org/W2147238549","https://openalex.org/W2148809531","https://openalex.org/W2151103935","https://openalex.org/W2163605009","https://openalex.org/W2164022341","https://openalex.org/W2170942078","https://openalex.org/W2174726731","https://openalex.org/W2204975001","https://openalex.org/W2292554763","https://openalex.org/W2295537791","https://openalex.org/W2952239967","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W1615295117","https://openalex.org/W2158102958","https://openalex.org/W2035094092","https://openalex.org/W2277784908","https://openalex.org/W2045213079","https://openalex.org/W2938717424","https://openalex.org/W2350926174","https://openalex.org/W2473933584","https://openalex.org/W2412408867","https://openalex.org/W2587721114"],"abstract_inverted_index":{"In":[0],"this":[1,79],"work,":[2],"we":[3,112],"propose":[4],"an":[5,31],"extension":[6],"of":[7,41,72,117],"established":[8],"image":[9,65,127],"retrieval":[10,128],"models":[11,21],"which":[12,22,54],"are":[13],"based":[14,97],"on":[15,20,98],"the":[16,39,47,56,69,75,115,118],"bag-of-words":[17],"representation,":[18],"i.e.":[19],"quantize":[23],"local":[24,42,85,91],"features":[25,43,100],"such":[26],"as":[27],"SIFT":[28],"to":[29,49,61],"leverage":[30],"inverted":[32],"file":[33],"indexing":[34],"scheme":[35],"for":[36],"speedup.":[37],"Since":[38],"quantization":[40],"impairs":[44],"their":[45],"discriminability,":[46],"ability":[48],"retrieve":[50],"those":[51],"database":[52],"images":[53,73],"show":[55],"same":[57],"object":[58],"or":[59],"scene":[60],"a":[62,83,95,125],"given":[63],"query":[64],"is":[66],"decreasing":[67],"with":[68,87],"growing":[70],"number":[71],"in":[74,124],"database.":[76],"We":[77],"address":[78],"issue":[80],"by":[81],"extending":[82],"quantized":[84],"feature":[86],"information":[88],"from":[89,101],"its":[90,121],"spatial":[92],"neighborhood":[93],"incorporating":[94],"representation":[96,119],"pooling":[99],"deep":[102],"convolutional":[103],"neural":[104],"network":[105],"layer":[106],"outputs.":[107],"Using":[108],"four":[109],"public":[110],"datasets,":[111],"evaluate":[113],"both":[114],"discriminability":[116],"and":[120],"overall":[122],"performance":[123],"large-scale":[126],"setup.":[129]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}