{"id":"https://openalex.org/W1963763607","doi":"https://doi.org/10.1145/1460096.1460151","title":"Perplexity-based evidential neural network classifier fusion using mpeg-7 low-level visual features","display_name":"Perplexity-based evidential neural network classifier fusion using mpeg-7 low-level visual features","publication_year":2008,"publication_date":"2008-10-30","ids":{"openalex":"https://openalex.org/W1963763607","doi":"https://doi.org/10.1145/1460096.1460151","mag":"1963763607"},"language":"en","primary_location":{"id":"doi:10.1145/1460096.1460151","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1460096.1460151","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM international conference on Multimedia information retrieval","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/A5108962343","display_name":"Rachid Benmokhtar","orcid":null},"institutions":[{"id":"https://openalex.org/I1902872","display_name":"EURECOM","ror":"https://ror.org/00sse7z02","country_code":"FR","type":"education","lineage":["https://openalex.org/I1902872","https://openalex.org/I205703379"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Rachid Benmokhtar","raw_affiliation_strings":["Institut EURECOM, Valbonne, France","Institut Eurecom, Valbonne, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut EURECOM, Valbonne, France","institution_ids":["https://openalex.org/I1902872"]},{"raw_affiliation_string":"Institut Eurecom, Valbonne, France","institution_ids":["https://openalex.org/I1902872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038148603","display_name":"Beno\u00eet Huet","orcid":"https://orcid.org/0000-0002-0608-6939"},"institutions":[{"id":"https://openalex.org/I1902872","display_name":"EURECOM","ror":"https://ror.org/00sse7z02","country_code":"FR","type":"education","lineage":["https://openalex.org/I1902872","https://openalex.org/I205703379"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Benoit Huet","raw_affiliation_strings":["Institut EURECOM, Valbonne, France","Institut Eurecom, Valbonne, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut EURECOM, Valbonne, France","institution_ids":["https://openalex.org/I1902872"]},{"raw_affiliation_string":"Institut Eurecom, Valbonne, France","institution_ids":["https://openalex.org/I1902872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1902872"],"apc_list":null,"apc_paid":null,"fwci":1.0427,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.74315051,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"336","last_page":"341"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9941999912261963,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9941999912261963,"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/T10057","display_name":"Face and Expression Recognition","score":0.9909999966621399,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9900000095367432,"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/perplexity","display_name":"Perplexity","score":0.9041807055473328},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7493941187858582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.678964376449585},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.49612101912498474},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4935997724533081},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46397170424461365},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4111321270465851},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32874196767807007},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3260268568992615},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.056680768728256226}],"concepts":[{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.9041807055473328},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7493941187858582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.678964376449585},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.49612101912498474},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4935997724533081},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46397170424461365},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4111321270465851},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32874196767807007},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3260268568992615},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.056680768728256226},{"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:10.1145/1460096.1460151","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1460096.1460151","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM international conference on Multimedia information retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6399999856948853,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W740415","https://openalex.org/W1485800236","https://openalex.org/W1876110941","https://openalex.org/W1945772893","https://openalex.org/W1972195523","https://openalex.org/W1974967573","https://openalex.org/W2042241913","https://openalex.org/W2048309930","https://openalex.org/W2063555871","https://openalex.org/W2102013158","https://openalex.org/W2120156058","https://openalex.org/W2141505131","https://openalex.org/W2154379196","https://openalex.org/W2156909104","https://openalex.org/W2917897246","https://openalex.org/W4230674625","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2376415519","https://openalex.org/W4294769427","https://openalex.org/W1601381279","https://openalex.org/W1895908943","https://openalex.org/W4225667838","https://openalex.org/W4281893144","https://openalex.org/W2374747083","https://openalex.org/W4388254351","https://openalex.org/W4386270999","https://openalex.org/W2982442115"],"abstract_inverted_index":{"In":[0],"this":[1,84],"paper,":[2],"an":[3,104],"automatic":[4],"content-based":[5],"video":[6,33],"shot":[7,59],"indexing":[8],"framework":[9,119],"is":[10,35,93],"proposed":[11,94,137],"employing":[12],"five":[13],"types":[14],"of":[15,29,39,57,66,120],"MPEG-7":[16],"low-level":[17],"visual":[18,75],"features":[19,30,125],"(color,":[20],"texture,":[21],"shape,":[22],"motion":[23],"and":[24,77,131],"face).":[25],"Once":[26],"the":[27,32,37,58,64,68,72,78,118,121,129,132,136],"set":[28],"representing":[31],"content":[34],"determined,":[36],"question":[38],"how":[40],"to":[41,48,51,102],"combine":[42],"their":[43],"individual":[44],"classifier":[45,106],"outputs":[46],"according":[47],"each":[49],"feature":[50,76],"form":[52],"a":[53,86],"final":[54],"semantic":[55,69,81],"decision":[56],"must":[60],"be":[61],"addressed,":[62],"in":[63,117],"goal":[65],"bridging":[67],"gap":[70],"between":[71],"low":[73],"level":[74,80,124],"high":[79,123],"concepts.":[82],"For":[83],"aim,":[85],"novel":[87],"approach":[88],"called":[89],"\"perplexity-based":[90],"weighted":[91],"descriptors\"":[92],"before":[95],"applying":[96],"our":[97],"evidential":[98],"combiner":[99],"NNET":[100],"[3],":[101],"obtain":[103],"adaptive":[105],"fusion":[107],"PENN":[108],"(Perplexity-based":[109],"Evidential":[110],"Neural":[111],"Network).":[112],"The":[113],"experimental":[114],"results":[115],"conducted":[116],"TRECVid'07":[122],"extraction":[126],"task":[127],"report":[128],"efficiency":[130],"improvement":[133],"provided":[134],"by":[135],"scheme.":[138]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":5}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
