{"id":"https://openalex.org/W3153565615","doi":"https://doi.org/10.3233/jifs-202249","title":"Filtration network: A frame sampling strategy via deep reinforcement learning for video captioning","display_name":"Filtration network: A frame sampling strategy via deep reinforcement learning for video captioning","publication_year":2021,"publication_date":"2021-04-20","ids":{"openalex":"https://openalex.org/W3153565615","doi":"https://doi.org/10.3233/jifs-202249","mag":"3153565615"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-202249","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-202249","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-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/A5076751421","display_name":"Tiancheng Qian","orcid":"https://orcid.org/0000-0002-4487-2789"},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiancheng Qian","raw_affiliation_strings":["College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101986286","display_name":"Xue Mei","orcid":"https://orcid.org/0000-0002-8237-1539"},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xue Mei","raw_affiliation_strings":["College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007885231","display_name":"Pengxiang Xu","orcid":"https://orcid.org/0000-0001-7630-2919"},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengxiang Xu","raw_affiliation_strings":["College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066905008","display_name":"Kangqi Ge","orcid":null},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kangqi Ge","raw_affiliation_strings":["College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014053645","display_name":"Zhelei Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhelei Qiu","raw_affiliation_strings":["College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101986286"],"corresponding_institution_ids":["https://openalex.org/I134687103"],"apc_list":null,"apc_paid":null,"fwci":0.2909,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53921885,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"40","issue":"6","first_page":"11085","last_page":"11097"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","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/T11714","display_name":"Multimodal Machine Learning Applications","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/T10812","display_name":"Human Pose and Action Recognition","score":0.9987999796867371,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9980999827384949,"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":0.8802751898765564},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6672590374946594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6255927085876465},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.6040960550308228},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5690312385559082},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.45280978083610535},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4335378408432007},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3495047688484192},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13576912879943848}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8802751898765564},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6672590374946594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6255927085876465},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.6040960550308228},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5690312385559082},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.45280978083610535},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4335378408432007},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3495047688484192},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13576912879943848},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-202249","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-202249","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2164290393","https://openalex.org/W2425121537","https://openalex.org/W2554906389","https://openalex.org/W2799176631","https://openalex.org/W2895845501","https://openalex.org/W2900395970","https://openalex.org/W2905145027","https://openalex.org/W2907145969","https://openalex.org/W2917052767","https://openalex.org/W2945223572","https://openalex.org/W2945961616","https://openalex.org/W2948358897","https://openalex.org/W2950579554","https://openalex.org/W2951390634","https://openalex.org/W2962990649","https://openalex.org/W2963929112","https://openalex.org/W2963971014","https://openalex.org/W2964206580","https://openalex.org/W2964241990","https://openalex.org/W2970060478","https://openalex.org/W2984862483","https://openalex.org/W3035365026"],"related_works":["https://openalex.org/W4210416330","https://openalex.org/W3088136942","https://openalex.org/W2949362007","https://openalex.org/W2775506363","https://openalex.org/W4290852288","https://openalex.org/W4388893791","https://openalex.org/W4283207562","https://openalex.org/W2963177403","https://openalex.org/W2330246314","https://openalex.org/W2949522393"],"abstract_inverted_index":{"Recently":[0],"many":[1],"methods":[2,18,175],"use":[3,20],"encoder-decoder":[4],"framework":[5],"for":[6],"video":[7],"captioning,":[8],"aiming":[9],"to":[10,68,77,91,141,146,165],"translate":[11],"short":[12],"videos":[13],"into":[14],"natural":[15],"language.":[16],"These":[17],"usually":[19],"equal":[21],"interval":[22],"frame":[23],"sampling.":[24],"However,":[25],"lacking":[26],"a":[27,34],"good":[28,167],"efficiency":[29],"in":[30,41,126,154,187],"sampling,":[31],"it":[32,129],"has":[33],"high":[35],"temporal":[36],"and":[37,112,123,171,195],"spatial":[38],"redundancy,":[39],"resulting":[40],"unnecessary":[42],"computation":[43],"cost.":[44],"In":[45,66],"addition,":[46],"the":[47,56,70,94,101,109,113,118],"existing":[48],"approaches":[49],"simply":[50],"splice":[51],"different":[52],"visual":[53,159],"features":[54,61,160],"on":[55,176],"fully":[57],"connection":[58],"layer.":[59],"Therefore,":[60],"cannot":[62],"be":[63],"effectively":[64],"utilized.":[65],"order":[67],"solve":[69],"defects,":[71],"we":[72],"proposed":[73],"filtration":[74],"network":[75,144],"(FN)":[76],"select":[78],"key":[79,137],"frames,":[80],"which":[81],"is":[82,99,105],"trained":[83],"by":[84,107,161],"deep":[85],"reinforcement":[86],"learning":[87],"algorithm":[88],"actor-double-critic.":[89],"According":[90],"behavior":[92,102],"psychology,":[93],"core":[95],"idea":[96],"of":[97,103,120,151,158,189],"actor-double-critic":[98],"that":[100,181],"agent":[104],"determined":[106],"both":[108],"external":[110],"environment":[111],"internal":[114],"personality.":[115],"It":[116],"avoids":[117],"phenomenon":[119],"unclear":[121],"reward":[122],"sparse":[124],"feedback":[125,132],"training":[127],"because":[128],"gives":[130],"steady":[131],"after":[133],"each":[134],"action.":[135],"The":[136,149],"frames":[138],"are":[139],"sent":[140],"combine":[142],"codec":[143],"(CCN)":[145],"generate":[147],"sentences.":[148],"operation":[150],"feature":[152],"combination":[153],"CCN":[155],"make":[156,166],"fusion":[157],"complex":[162],"number":[163],"representation":[164],"semantic":[168],"modeling.":[169],"Experiments":[170],"comparisons":[172],"with":[173],"other":[174],"two":[177],"datasets":[178],"(MSVD/MSR-VTT)":[179],"show":[180],"our":[182],"approach":[183],"achieves":[184],"better":[185],"performance":[186],"terms":[188],"four":[190],"metrics,":[191],"BLEU-4,":[192],"METEOR,":[193],"ROUGE-L":[194],"CIDEr.":[196]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}