{"id":"https://openalex.org/W1989250726","doi":"https://doi.org/10.1109/cbmi.2014.6849817","title":"Using semantic features to improve large-scale visual concept detection","display_name":"Using semantic features to improve large-scale visual concept detection","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W1989250726","doi":"https://doi.org/10.1109/cbmi.2014.6849817","mag":"1989250726"},"language":"en","primary_location":{"id":"doi:10.1109/cbmi.2014.6849817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbmi.2014.6849817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI)","raw_type":"proceedings-article"},"type":"article","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/A5028154958","display_name":"Mats Sj\u00f6berg","orcid":"https://orcid.org/0000-0002-3157-7668"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Mats Sjoberg","raw_affiliation_strings":["Department of Information and Computer Science, Aalto University School of Science, Espoo, Finland","Sch. of Sci., Dept. of Inf. & Comput. Sci., Aalto Univ., Espoo, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Information and Computer Science, Aalto University School of Science, Espoo, Finland","institution_ids":["https://openalex.org/I9927081"]},{"raw_affiliation_string":"Sch. of Sci., Dept. of Inf. & Comput. Sci., Aalto Univ., Espoo, Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036133390","display_name":"Jorma Laaksonen","orcid":"https://orcid.org/0000-0001-7218-3131"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Jorma Laaksonen","raw_affiliation_strings":["Department of Information and Computer Science, Aalto University School of Science, Espoo, Finland","Sch. of Sci., Dept. of Inf. & Comput. Sci., Aalto Univ., Espoo, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Information and Computer Science, Aalto University School of Science, Espoo, Finland","institution_ids":["https://openalex.org/I9927081"]},{"raw_affiliation_string":"Sch. of Sci., Dept. of Inf. & Comput. Sci., Aalto Univ., Espoo, Finland","institution_ids":["https://openalex.org/I9927081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5028154958"],"corresponding_institution_ids":["https://openalex.org/I9927081"],"apc_list":null,"apc_paid":null,"fwci":0.7316,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74227706,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"9","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":0.9998000264167786,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9983999729156494,"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":0.9922000169754028,"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":0.8599107265472412},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.666147768497467},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6162001490592957},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5749388337135315},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5603278279304504},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5159781575202942},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5101683139801025},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5092564821243286},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4566669762134552},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4520823359489441},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.43810003995895386},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4341806173324585},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4259011149406433},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3663935661315918},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.33604416251182556},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3219729959964752}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8599107265472412},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.666147768497467},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6162001490592957},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5749388337135315},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5603278279304504},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5159781575202942},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5101683139801025},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5092564821243286},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4566669762134552},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4520823359489441},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.43810003995895386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4341806173324585},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4259011149406433},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3663935661315918},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33604416251182556},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3219729959964752},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/cbmi.2014.6849817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbmi.2014.6849817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321108","display_name":"Academy of Finland","ror":"https://ror.org/05k73zm37"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W120589563","https://openalex.org/W172303158","https://openalex.org/W1604693401","https://openalex.org/W1605811577","https://openalex.org/W1607586839","https://openalex.org/W1679913846","https://openalex.org/W2018668305","https://openalex.org/W2033455808","https://openalex.org/W2056138155","https://openalex.org/W2062903088","https://openalex.org/W2063555871","https://openalex.org/W2080846962","https://openalex.org/W2115536324","https://openalex.org/W2118585731","https://openalex.org/W2122528955","https://openalex.org/W2125829867","https://openalex.org/W2128841997","https://openalex.org/W2139495941","https://openalex.org/W2147502347","https://openalex.org/W2153635508","https://openalex.org/W2162762921","https://openalex.org/W2169177311","https://openalex.org/W2170942078","https://openalex.org/W3120421331","https://openalex.org/W4213332169","https://openalex.org/W4252911702","https://openalex.org/W4285719527","https://openalex.org/W6604983722","https://openalex.org/W6606961583","https://openalex.org/W6636038317","https://openalex.org/W6677656871","https://openalex.org/W6678145947","https://openalex.org/W6680571270","https://openalex.org/W6684872329"],"related_works":["https://openalex.org/W1493568480","https://openalex.org/W4385967523","https://openalex.org/W4391382592","https://openalex.org/W2995727521","https://openalex.org/W4387253492","https://openalex.org/W2997877535","https://openalex.org/W4308080241","https://openalex.org/W4205668735","https://openalex.org/W2380708104","https://openalex.org/W4390871823"],"abstract_inverted_index":{"Currently":[0],"there":[1],"are":[2,22],"many":[3],"multimedia":[4],"benchmarks":[5],"and":[6,81,115,149],"databases":[7],"available":[8],"with":[9,75,83,132],"a":[10,119,140],"predefined":[11],"set":[12],"of":[13,58,78],"concepts":[14,31,66],"for":[15,37,63],"which":[16,144],"detectors":[17],"can":[18,27,93],"be":[19,109],"formed":[20],"or":[21,40],"even":[23],"already":[24],"available.":[25],"One":[26],"use":[28,57],"these":[29],"background":[30],"to":[32],"form":[33],"semantic":[34,60,134],"concept":[35,48,61,135],"vectors":[36],"each":[38],"image":[39],"video":[41,79],"in":[42,67,111],"the":[43,47,56,71,90,112,133],"database":[44],"by":[45],"concatenating":[46],"prediction":[49],"outputs.":[50],"In":[51,101],"this":[52],"paper":[53],"we":[54,128],"investigate":[55],"such":[59],"features":[62,99,131],"detecting":[64],"novel":[65],"two":[68],"large-scale":[69],"experiments:":[70],"TRECVID":[72],"2012":[73],"evaluation":[74],"800":[76],"hours":[77],"data,":[80],"MIRFLICKR":[82],"1":[84],"million":[85],"images.":[86],"We":[87,137],"show":[88,118],"that":[89],"detection":[91,113,148],"performance":[92],"improve":[94],"significantly":[95],"over":[96],"using":[97,123],"visual":[98,130],"only.":[100],"some":[102],"applications,":[103],"computationally":[104],"expensive":[105],"kernel":[106],"classifiers":[107,126],"cannot":[108],"used":[110],"phase,":[114],"our":[116],"experiments":[117],"consistent":[120],"significant":[121],"improvement":[122],"fast":[124,146],"linear":[125],"when":[127],"replace":[129],"feature.":[136],"also":[138],"propose":[139],"Self-Organising":[141],"Map-based":[142],"method":[143],"affords":[145],"training-free":[147],"intuitive":[150],"visualisation":[151],"properties.":[152]},"counts_by_year":[{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}