{"id":"https://openalex.org/W4407758118","doi":"https://doi.org/10.1080/08839514.2025.2462382","title":"DHMDL: Dynamically Hashed Multimodal Deep Learning Framework for Racket Video Summarization Using Audio and Visual Markers","display_name":"DHMDL: Dynamically Hashed Multimodal Deep Learning Framework for Racket Video Summarization Using Audio and Visual Markers","publication_year":2025,"publication_date":"2025-02-18","ids":{"openalex":"https://openalex.org/W4407758118","doi":"https://doi.org/10.1080/08839514.2025.2462382"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2025.2462382","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2025.2462382","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1080/08839514.2025.2462382","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011537875","display_name":"Priyanka Ganesan","orcid":"https://orcid.org/0000-0001-6961-2994"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"G. Priyanka","raw_affiliation_strings":["Mepco Schenk Engineering College"],"raw_orcid":"https://orcid.org/0000-0001-6961-2994","affiliations":[{"raw_affiliation_string":"Mepco Schenk Engineering College","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054204378","display_name":"J. Senthilkumar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"J. Senthil Kumar","raw_affiliation_strings":["Mepco Schenk Engineering College"],"raw_orcid":"https://orcid.org/0000-0002-9516-0327","affiliations":[{"raw_affiliation_string":"Mepco Schenk Engineering College","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044628030","display_name":"Mrs. M. Prasha Meena","orcid":"https://orcid.org/0009-0007-4503-0704"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M. Prasha Meena","raw_affiliation_strings":["Mepco Schenk Engineering College"],"raw_orcid":"https://orcid.org/0009-0007-4503-0704","affiliations":[{"raw_affiliation_string":"Mepco Schenk Engineering College","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011537875"],"corresponding_institution_ids":[],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":2.5506,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.86684073,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"39","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9997000098228455,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9882000088691711,"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":0.9043450355529785},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.8693047761917114},{"id":"https://openalex.org/keywords/racket","display_name":"Racket","score":0.6909292340278625},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6002236008644104},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4539092481136322},{"id":"https://openalex.org/keywords/audio-visual","display_name":"Audio visual","score":0.4348789155483246},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4145791828632355},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.38385894894599915},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3495073914527893},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.30748268961906433},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.18727168440818787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9043450355529785},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8693047761917114},{"id":"https://openalex.org/C2778707667","wikidata":"https://www.wikidata.org/wiki/Q1254148","display_name":"Racket","level":3,"score":0.6909292340278625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6002236008644104},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4539092481136322},{"id":"https://openalex.org/C3017588708","wikidata":"https://www.wikidata.org/wiki/Q758901","display_name":"Audio visual","level":2,"score":0.4348789155483246},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4145791828632355},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.38385894894599915},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3495073914527893},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.30748268961906433},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.18727168440818787},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2025.2462382","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2025.2462382","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:40fd945e904649469482598f30cf8bee","is_oa":true,"landing_page_url":"https://doaj.org/article/40fd945e904649469482598f30cf8bee","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 39, Iss 1 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/08839514.2025.2462382","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2025.2462382","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":96,"referenced_works":["https://openalex.org/W1987366351","https://openalex.org/W1994864760","https://openalex.org/W1995562189","https://openalex.org/W2026012689","https://openalex.org/W2030465255","https://openalex.org/W2048962186","https://openalex.org/W2049466529","https://openalex.org/W2089959764","https://openalex.org/W2103943262","https://openalex.org/W2117849405","https://openalex.org/W2129175997","https://openalex.org/W2141858776","https://openalex.org/W2142824200","https://openalex.org/W2145652192","https://openalex.org/W2171415520","https://openalex.org/W2243691486","https://openalex.org/W2337527070","https://openalex.org/W2341528187","https://openalex.org/W2399467634","https://openalex.org/W2514348320","https://openalex.org/W2529165750","https://openalex.org/W2529272619","https://openalex.org/W2544224704","https://openalex.org/W2766827306","https://openalex.org/W2767188786","https://openalex.org/W2783750485","https://openalex.org/W2789931190","https://openalex.org/W2793286954","https://openalex.org/W2883872876","https://openalex.org/W2897230578","https://openalex.org/W2906430987","https://openalex.org/W2908469318","https://openalex.org/W2962837596","https://openalex.org/W2962849599","https://openalex.org/W2963670497","https://openalex.org/W2964167369","https://openalex.org/W2969844053","https://openalex.org/W2970049315","https://openalex.org/W2973843264","https://openalex.org/W2987372042","https://openalex.org/W2996611683","https://openalex.org/W3004657710","https://openalex.org/W3010790568","https://openalex.org/W3011696708","https://openalex.org/W3025569967","https://openalex.org/W3036900224","https://openalex.org/W3037747636","https://openalex.org/W3053202119","https://openalex.org/W3080272091","https://openalex.org/W3091145949","https://openalex.org/W3092226176","https://openalex.org/W3099156605","https://openalex.org/W3101998545","https://openalex.org/W3103375915","https://openalex.org/W3107128832","https://openalex.org/W3116333165","https://openalex.org/W3136517319","https://openalex.org/W3136873339","https://openalex.org/W3150815828","https://openalex.org/W3159589496","https://openalex.org/W3164744211","https://openalex.org/W3168973268","https://openalex.org/W3170468650","https://openalex.org/W3171536535","https://openalex.org/W3174989968","https://openalex.org/W3176372653","https://openalex.org/W3178880767","https://openalex.org/W3190350044","https://openalex.org/W3202360802","https://openalex.org/W3208041321","https://openalex.org/W4210246006","https://openalex.org/W4210333049","https://openalex.org/W4221002449","https://openalex.org/W4221148492","https://openalex.org/W4225769600","https://openalex.org/W4225856951","https://openalex.org/W4225925355","https://openalex.org/W4226410466","https://openalex.org/W4235440014","https://openalex.org/W4236965008","https://openalex.org/W4281664351","https://openalex.org/W4283739917","https://openalex.org/W4285022937","https://openalex.org/W4285251800","https://openalex.org/W4285256271","https://openalex.org/W4293665662","https://openalex.org/W4298205916","https://openalex.org/W4298326407","https://openalex.org/W4312906155","https://openalex.org/W4313004955","https://openalex.org/W4320016134","https://openalex.org/W4360979827","https://openalex.org/W4362597616","https://openalex.org/W4385779901","https://openalex.org/W4390452903","https://openalex.org/W4390655812"],"related_works":["https://openalex.org/W2744434216","https://openalex.org/W2744749537","https://openalex.org/W598786559","https://openalex.org/W2489491829","https://openalex.org/W2744275524","https://openalex.org/W2589774136","https://openalex.org/W2580283794","https://openalex.org/W2593983340","https://openalex.org/W2370107557","https://openalex.org/W2366403280"],"abstract_inverted_index":{"Sports":[0],"videos":[1,158],"are":[2],"being":[3],"streamed":[4],"over":[5,65],"a":[6,17,35],"large":[7],"range":[8],"of":[9,55,119],"social":[10],"media":[11],"platforms,":[12],"and":[13,21,99,102,155,159],"they":[14],"always":[15],"have":[16,50],"huge":[18],"audience":[19],"base":[20],"viewer":[22],"history.":[23],"In":[24],"order":[25],"to":[26,88,105,116],"provide":[27],"more":[28],"excitement":[29,81,120,141],"for":[30,138],"the":[31,52,56,123,134,140,160],"users":[32],"in":[33,145],"watching":[34],"completed":[36],"game,":[37],"automatic":[38],"video":[39,57,77,107,146],"summarization":[40,58,78],"is":[41,143,150],"an":[42],"inevitable":[43],"solution.":[44],"While":[45],"sports":[46,76],"like":[47],"soccer,":[48],"cricket":[49],"been":[51,63],"main":[53],"focus":[54],"research,":[59],"little":[60],"attention":[61],"has":[62],"centered":[64],"racket":[66],"sports.":[67],"Our":[68],"proposed":[69,124],"dynamically":[70],"hashed":[71],"multimodal":[72],"deep":[73,85],"learning":[74,86],"(DHMDL)":[75],"framework":[79,149],"fuses":[80],"scores":[82,142],"by":[83,111,176,184],"utilizing":[84],"architectures":[87],"extract":[89],"cues":[90],"from":[91],"multi":[92],"modalities":[93],"namely":[94],"commentator":[95],"voice,":[96],"spectators\u2019":[97],"cheers":[98],"player\u2019s":[100],"expression":[101],"then":[103],"leverages":[104],"generate":[106],"segment":[108,181],"as":[109],"highlight":[110,180],"using":[112,133],"hash":[113,130],"codes":[114],"mapped":[115],"weighted":[117],"sum":[118],"score.":[121],"Also,":[122],"synchronized":[125],"parallel":[126],"processing":[127],"ranking":[128],"based":[129],"map":[131],"framed":[132],"merge":[135],"sorting":[136],"technique":[137],"categorizing":[139],"applied":[144],"summarization.":[147],"The":[148],"tested":[151],"on":[152,186],"U.S.":[153],"Open":[154],"Wimbledon":[156],"match":[157],"results":[161,164],"show":[162],"superior":[163],"against":[165],"state-of-art":[166],"techniques":[167],"with":[168],"normalized":[169],"discounted":[170],"cumulative":[171],"gain":[172],"(nDCG)":[173],"score":[174],"improved":[175],"2%,":[177],"positive":[178],"matching":[179],"identification":[182],"increased":[183],"20%":[185],"YouTube":[187],"Videos.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
