{"id":"https://openalex.org/W4381049901","doi":"https://doi.org/10.1109/tgrs.2023.3281334","title":"Improving Image Captioning Systems With Postprocessing Strategies","display_name":"Improving Image Captioning Systems With Postprocessing Strategies","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4381049901","doi":"https://doi.org/10.1109/tgrs.2023.3281334"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3281334","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3281334","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","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/A5007505274","display_name":"Genc Hoxha","orcid":"https://orcid.org/0000-0003-2552-5615"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Genc Hoxha","raw_affiliation_strings":["Faculty of Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0003-2552-5615","affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092191347","display_name":"Giacomo Scuccato","orcid":null},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giacomo Scuccato","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021389231","display_name":"Farid Melgani","orcid":"https://orcid.org/0000-0001-9745-3732"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Farid Melgani","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy"],"raw_orcid":"https://orcid.org/0000-0001-9745-3732","affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007505274"],"corresponding_institution_ids":["https://openalex.org/I4577782"],"apc_list":null,"apc_paid":null,"fwci":2.0017,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.8860249,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"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":1.0,"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":0.9987999796867371,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.8651025295257568},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.8565767407417297},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6986818909645081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5868211388587952},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5812968015670776},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5570253729820251},{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.48315852880477905},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.43807679414749146},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4345412254333496},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4270560145378113},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.42153021693229675},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41732969880104065},{"id":"https://openalex.org/keywords/viterbi-decoder","display_name":"Viterbi decoder","score":0.41310185194015503},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40335753560066223},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32767000794410706},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3237917423248291},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3047834038734436},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19499236345291138}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8651025295257568},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.8565767407417297},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6986818909645081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5868211388587952},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5812968015670776},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5570253729820251},{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.48315852880477905},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.43807679414749146},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4345412254333496},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4270560145378113},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.42153021693229675},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41732969880104065},{"id":"https://openalex.org/C117379686","wikidata":"https://www.wikidata.org/wiki/Q6996459","display_name":"Viterbi decoder","level":3,"score":0.41310185194015503},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40335753560066223},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32767000794410706},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3237917423248291},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3047834038734436},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19499236345291138},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2023.3281334","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3281334","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:iris.unitn.it:11572/400699","is_oa":false,"landing_page_url":"https://hdl.handle.net/11572/400699","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"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":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1895577753","https://openalex.org/W1897761818","https://openalex.org/W1956340063","https://openalex.org/W1969616664","https://openalex.org/W1980038761","https://openalex.org/W1991133427","https://openalex.org/W2064675550","https://openalex.org/W2086866337","https://openalex.org/W2108598243","https://openalex.org/W2123301721","https://openalex.org/W2125838338","https://openalex.org/W2142384583","https://openalex.org/W2154652894","https://openalex.org/W2157331557","https://openalex.org/W2159243025","https://openalex.org/W2244457783","https://openalex.org/W2510520237","https://openalex.org/W2603566245","https://openalex.org/W2779054585","https://openalex.org/W2911584214","https://openalex.org/W2920981979","https://openalex.org/W2953322005","https://openalex.org/W2963686907","https://openalex.org/W2995904231","https://openalex.org/W2997056851","https://openalex.org/W3006487741","https://openalex.org/W3016776421","https://openalex.org/W3017628311","https://openalex.org/W3033783894","https://openalex.org/W3034075748","https://openalex.org/W3038038411","https://openalex.org/W3042724941","https://openalex.org/W3046260628","https://openalex.org/W3047058320","https://openalex.org/W3097754216","https://openalex.org/W3100245404","https://openalex.org/W3105531629","https://openalex.org/W3154766321","https://openalex.org/W3196922338","https://openalex.org/W3207977110","https://openalex.org/W3213119051","https://openalex.org/W4213449032","https://openalex.org/W4289537913","https://openalex.org/W4292171200","https://openalex.org/W4293508747","https://openalex.org/W4310459386","https://openalex.org/W4312389717","https://openalex.org/W6630875275","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6678262379","https://openalex.org/W6682631176","https://openalex.org/W6683512859","https://openalex.org/W6725582241","https://openalex.org/W6898505805"],"related_works":["https://openalex.org/W2136652457","https://openalex.org/W2169849734","https://openalex.org/W2102309991","https://openalex.org/W2116722627","https://openalex.org/W2129150969","https://openalex.org/W1975869217","https://openalex.org/W2236912844","https://openalex.org/W1795315578","https://openalex.org/W2373954783","https://openalex.org/W2133857928"],"abstract_inverted_index":{"Image":[0],"captioning":[1],"(IC)":[2],"systems":[3],"are":[4,15,121,144,213],"generally":[5],"based":[6,122],"on":[7,123,183],"encoder\u2013decoder":[8,140,204],"architecture":[9],"where":[10],"convolutional":[11],"neural":[12,26],"networks":[13,27],"(CNNs)":[14],"employed":[16],"to":[17,44,66,105,109,138,159,197],"represent":[18],"an":[19,78],"image":[20],"with":[21],"discriminative":[22],"features":[23],"and":[24,69,113,128,215],"recurrent":[25,87],"(RNNs)":[28],"sequentially":[29],"generate":[30],"a":[31,36,161,202],"sentence":[32,162],"description.":[33],"Even":[34],"though":[35],"lot":[37],"of":[38,89,175,192,201],"effort":[39],"has":[40],"been":[41],"devoted":[42],"lately":[43],"designing":[45],"reliable":[46],"IC":[47,141,151,186,220],"systems,":[48],"the":[49,67,70,74,86,90,106,111,150,176,189,193,199],"task":[50],"is":[51,153,165],"far":[52],"from":[53],"being":[54],"solved.":[55],"The":[56,117,131,210],"generated":[57,107,167],"descriptions":[58,108],"can":[59,82,135],"be":[60,83,136],"affected":[61],"by":[62,205],"different":[63,185],"errors":[64,112],"related":[65],"attributes":[68],"objects":[71],"present":[72],"in":[73,85],"scene.":[75],"Moreover,":[76],"once":[77,149,163],"error":[79],"occurs,":[80],"it":[81,164],"propagated":[84],"layers":[88],"decoder":[91],"generating":[92,206],"non-accurate":[93],"descriptions.":[94,209],"To":[95],"solve":[96],"this":[97],"problem,":[98],"we":[99,157],"propose":[100,158],"two":[101],"postprocessing":[102,119,133,195],"strategies":[103,120,134,196],"applied":[104,137,145],"rectify":[110,160,198],"improve":[114],"their":[115],"quality.":[116],"proposed":[118,132,194],"hidden":[124],"Markov":[125],"models":[126],"(HMMs)":[127],"Viterbi":[129],"algorithm.":[130],"any":[139],"system.":[142],"They":[143],"at":[146,171],"test":[147],"time":[148,173],"system":[152],"trained.":[154],"In":[155],"particular,":[156],"fully":[166],"(post-generation":[168],"strategy)":[169],"or":[170],"each":[172],"instant":[174],"generation":[177],"process":[178],"(in-generation":[179],"strategy).":[180],"Experiments":[181],"conducted":[182],"four":[184],"datasets":[187],"confirm":[188],"promising":[190],"capabilities":[191],"output":[200],"simple":[203],"more":[207],"coherent":[208],"achieved":[211],"results":[212],"competitive":[214],"sometimes":[216],"better":[217],"than":[218],"complex":[219],"systems.":[221]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}