{"id":"https://openalex.org/W4214591501","doi":"https://doi.org/10.1145/3488933.3488941","title":"An Efficient Image Captioning Method Based on Generative Adversarial Networks","display_name":"An Efficient Image Captioning Method Based on Generative Adversarial Networks","publication_year":2021,"publication_date":"2021-09-24","ids":{"openalex":"https://openalex.org/W4214591501","doi":"https://doi.org/10.1145/3488933.3488941"},"language":"en","primary_location":{"id":"doi:10.1145/3488933.3488941","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488933.3488941","pdf_url":null,"source":{"id":"https://openalex.org/S4363608564","display_name":"2021 4th International Conference on Artificial Intelligence and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 4th International Conference on Artificial Intelligence and Pattern Recognition","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/A5100881436","display_name":"Lin Zhenxian","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Zhenxian","raw_affiliation_strings":["School of Science,Xi'an University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Science,Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084343751","display_name":"Feng Feirong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Feirong","raw_affiliation_strings":["School of Telecommunication and Information Engineering,Xi'an University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Telecommunication and Information Engineering,Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yang Xiaobao","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]},{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Xiaobao","raw_affiliation_strings":["School of Computer Science and Technology,Northwestern Polytechnical University,China., China and School of Computer Science and Technology,Xi'an University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology,Northwestern Polytechnical University,China., China and School of Computer Science and Technology,Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859","https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011372918","display_name":"Chen Ding","orcid":"https://orcid.org/0000-0001-8101-5738"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ding Chen","raw_affiliation_strings":["School of Computer Science and Technology,Xi'an University of Posts and Telecommunications,China, China and Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing,Xi'an University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology,Xi'an University of Posts and Telecommunications,China, China and Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing,Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100881436"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.1314,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53063269,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"374","last_page":"379"},"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":0.9955000281333923,"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":0.9925000071525574,"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/closed-captioning","display_name":"Closed captioning","score":0.9133192300796509},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7947633862495422},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.773400068283081},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.641419529914856},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.47467875480651855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47212275862693787},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47058194875717163},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.44588226079940796},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4441305696964264},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4214274287223816},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34207963943481445},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3204282820224762},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15711233019828796},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.069509357213974}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.9133192300796509},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7947633862495422},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.773400068283081},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.641419529914856},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.47467875480651855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47212275862693787},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47058194875717163},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.44588226079940796},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4441305696964264},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4214274287223816},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34207963943481445},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3204282820224762},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15711233019828796},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.069509357213974},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3488933.3488941","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488933.3488941","pdf_url":null,"source":{"id":"https://openalex.org/S4363608564","display_name":"2021 4th International Conference on Artificial Intelligence and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 4th International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1514535095","https://openalex.org/W1686810756","https://openalex.org/W1895577753","https://openalex.org/W2064675550","https://openalex.org/W2101105183","https://openalex.org/W2125389028","https://openalex.org/W2147800946","https://openalex.org/W2155027007","https://openalex.org/W2157331557","https://openalex.org/W2159243025","https://openalex.org/W2194775991","https://openalex.org/W2293185259","https://openalex.org/W2611862713","https://openalex.org/W2751804245","https://openalex.org/W2800782462","https://openalex.org/W2803525166","https://openalex.org/W2945222541","https://openalex.org/W2946948417","https://openalex.org/W2950626540","https://openalex.org/W2955956881","https://openalex.org/W2962968835","https://openalex.org/W2964268978","https://openalex.org/W2968660381","https://openalex.org/W2971960766","https://openalex.org/W2990069284","https://openalex.org/W2996202528","https://openalex.org/W3004754991","https://openalex.org/W3014791201","https://openalex.org/W3019057642","https://openalex.org/W3041579038"],"related_works":["https://openalex.org/W4210416330","https://openalex.org/W2775506363","https://openalex.org/W3088136942","https://openalex.org/W4290852288","https://openalex.org/W2949362007","https://openalex.org/W4388893791","https://openalex.org/W4283207562","https://openalex.org/W2963177403","https://openalex.org/W2330246314","https://openalex.org/W2949522393"],"abstract_inverted_index":{"Image":[0],"captioning":[1,84],"is":[2,52,134],"usually":[3],"based":[4,86],"on":[5,87,114],"the":[6,10,13,16,20,24,33,36,40,46,63,70,73,97,107,126],"mainstream":[7],"encoder-decoder":[8,67,153],"framework,":[9],"accuracy":[11],"of":[12,19,26,65,72,80,121],"encoders":[14,34,98],"and":[15,35,49,58,94],"generation":[17],"capability":[18],"decoders":[21,37,108],"directly":[22],"affect":[23],"quality":[25,71],"image":[27,83,101],"captions.":[28,158],"But":[29],"no":[30],"matter":[31],"how":[32],"are":[38],"combined,":[39],"generated":[41,74],"captions":[42,60],"will":[43],"only":[44],"imitate":[45],"ground-truth":[47],"captions,":[48,75,111],"its":[50],"diversity":[51],"suppressed.":[53],"To":[54],"generate":[55,110],"more":[56],"accurate":[57],"diverse":[59,157],"while":[61],"exploring":[62],"impact":[64],"different":[66],"frameworks":[68],"for":[69,155],"we":[76,90],"conducted":[77],"an":[78,81,151],"exploration":[79],"efficient":[82,152],"method":[85],"GAN.":[88],"Specifically,":[89],"use":[91],"ResNet152,":[92],"EfficientNet-B0,":[93],"EfficientNet-B2":[95],"as":[96,106,150],"to":[99,109],"extract":[100],"features,":[102],"GRU":[103],"or":[104],"Transformer":[105],"respectively.":[112],"Based":[113],"MS":[115],"COCO2014":[116],"dataset,":[117],"a":[118],"large":[119],"number":[120],"experiment":[122],"results":[123],"show":[124],"that":[125],"EfficientNet-B2+GRU":[127],"framework":[128,154],"has":[129],"best":[130],"performance,":[131],"training":[132],"time":[133],"reduced,":[135],"BLUE-4":[136],"score":[137],"increases":[138],"by":[139,143],"0.6,":[140],"parameters":[141],"reduce":[142],"0.66":[144],"million,":[145],"which":[146],"can":[147],"be":[148],"used":[149],"generating":[156]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}