{"id":"https://openalex.org/W4402351588","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650955","title":"Lightweight Super-Resolution for Chinese Scene Images Incorporating Textual Semantic Priors","display_name":"Lightweight Super-Resolution for Chinese Scene Images Incorporating Textual Semantic Priors","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402351588","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650955"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650955","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650955","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5008963281","display_name":"Zhouxin Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I163151501","display_name":"Hangzhou Normal University","ror":"https://ror.org/014v1mr15","country_code":"CN","type":"education","lineage":["https://openalex.org/I163151501"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhouxin Lu","raw_affiliation_strings":["Hangzhou Normal University,School of Information Science and Technology,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Normal University,School of Information Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I163151501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100341636","display_name":"Ben Wang","orcid":"https://orcid.org/0000-0002-5341-1642"},"institutions":[{"id":"https://openalex.org/I163151501","display_name":"Hangzhou Normal University","ror":"https://ror.org/014v1mr15","country_code":"CN","type":"education","lineage":["https://openalex.org/I163151501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ben Wang","raw_affiliation_strings":["Hangzhou Normal University,School of Information Science and Technology,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Normal University,School of Information Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I163151501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084854948","display_name":"Shuifa Sun","orcid":"https://orcid.org/0000-0003-0933-152X"},"institutions":[{"id":"https://openalex.org/I163151501","display_name":"Hangzhou Normal University","ror":"https://ror.org/014v1mr15","country_code":"CN","type":"education","lineage":["https://openalex.org/I163151501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuifa Sun","raw_affiliation_strings":["Hangzhou Normal University,School of Information Science and Technology,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Normal University,School of Information Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I163151501"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078102984","display_name":"Yongheng Tang","orcid":"https://orcid.org/0000-0002-3184-691X"},"institutions":[{"id":"https://openalex.org/I161350542","display_name":"China Three Gorges University","ror":"https://ror.org/0419nfc77","country_code":"CN","type":"education","lineage":["https://openalex.org/I161350542"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongheng Tang","raw_affiliation_strings":["China Three Gorges University,College of Computer and Information Technology,Yichang,China"],"affiliations":[{"raw_affiliation_string":"China Three Gorges University,College of Computer and Information Technology,Yichang,China","institution_ids":["https://openalex.org/I161350542"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5008963281"],"corresponding_institution_ids":["https://openalex.org/I163151501"],"apc_list":null,"apc_paid":null,"fwci":0.2624,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53119123,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","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/T10531","display_name":"Advanced Vision and Imaging","score":0.9987000226974487,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9965999722480774,"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":0.7366626262664795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6869456171989441},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6342698931694031},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.6100855469703674},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5125219821929932},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.43364790081977844},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.42403554916381836},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3700130581855774},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36786866188049316},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.1456259787082672}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7366626262664795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6869456171989441},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6342698931694031},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.6100855469703674},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5125219821929932},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43364790081977844},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.42403554916381836},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3700130581855774},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36786866188049316},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.1456259787082672}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650955","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650955","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W603536130","https://openalex.org/W2133665775","https://openalex.org/W2152404931","https://openalex.org/W2295124130","https://openalex.org/W2476548250","https://openalex.org/W2962834855","https://openalex.org/W2963163009","https://openalex.org/W2963645458","https://openalex.org/W2972424968","https://openalex.org/W3103667010","https://openalex.org/W3107840264","https://openalex.org/W3109807916","https://openalex.org/W3164382044","https://openalex.org/W3174746398","https://openalex.org/W3177505580","https://openalex.org/W3207918547","https://openalex.org/W4226374800","https://openalex.org/W4226544595","https://openalex.org/W4285606401","https://openalex.org/W4300978573","https://openalex.org/W4312923907","https://openalex.org/W4382240051","https://openalex.org/W4385245566","https://openalex.org/W4386075509"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W3122088529","https://openalex.org/W3041320102","https://openalex.org/W2143529858","https://openalex.org/W4367590696","https://openalex.org/W2056165575","https://openalex.org/W2358774654"],"abstract_inverted_index":{"In":[0,88],"the":[1,13,16,20,24,33,37,56,79,185,215,219],"fields":[2],"of":[3,15,58,81,208],"autonomous":[4],"driving":[5],"and":[6,22,29,39,75,111,121,137,167,183,212],"robotics,":[7],"text":[8,27,31,49,61,98,112,122,147,191,221],"image":[9,17,50,99,108,119,150,210],"super-resolution":[10,51,100],"can":[11],"improve":[12,36],"resolution":[14],"obtained":[18],"by":[19],"device,":[21],"help":[23],"system":[25],"capture":[26],"details":[28],"long-distance":[30],"in":[32,47,52,72,85,206,218],"scene":[34,97,198],"to":[35,68,90,116,144,162,180],"perception":[38],"decision-making":[40],"ability.":[41],"Significant":[42],"progress":[43],"has":[44],"been":[45],"made":[46],"prior-based":[48],"recent":[53],"years.":[54],"However,":[55],"fusion":[57],"complex":[59],"languages":[60],"prior":[62],"information,":[63],"such":[64],"as":[65],"Chinese,":[66],"leads":[67],"a":[69,95,173,196],"sharp":[70],"increase":[71],"network":[73],"parameters":[74],"computational":[76],"costs,":[77],"limiting":[78],"application":[80],"resource-constrained":[82],"mobile":[83],"robots":[84],"corresponding":[86],"scenarios.":[87],"response":[89],"this":[91],"issue,":[92],"we":[93],"propose":[94],"lightweight":[96],"method":[101],"that":[102,201],"incorporates":[103],"semantic":[104],"priors":[105],"(MPT-TISR).":[106],"Firstly,":[107],"convolutional":[109],"layer":[110],"recognizer":[113],"are":[114],"employed":[115],"extract":[117],"low-resolution":[118],"features":[120,166],"sequences,":[123],"respectively.":[124],"Then,":[125],"an":[126,153],"efficient":[127],"Text":[128],"Semantic":[129],"Feature":[130],"Fusion":[131],"Block":[132,158],"(FPCAT)":[133],"based":[134],"on":[135,190,195],"Transformers":[136],"Principal":[138],"Component":[139],"Analysis":[140],"(PCA)":[141],"is":[142,160,178],"constructed":[143],"associate":[145],"essential":[146],"information":[148],"with":[149],"features.":[151],"Simultaneously,":[152],"improved":[154],"MobileViTv3-based":[155],"Sequential":[156],"Residual":[157],"(SRBMVT3+)":[159],"designed":[161],"learn":[163],"high-dimensional":[164],"deep":[165],"enhance":[168],"feature":[169],"representation":[170],"capabilities.":[171],"Additionally,":[172],"binary":[174],"gradient":[175],"loss":[176],"function":[177],"utilized":[179],"filter":[181],"noise":[182],"guide":[184],"reconstruction":[186],"process":[187],"towards":[188],"focusing":[189],"details.":[192],"Experimental":[193],"results":[194],"Chinese":[197],"dataset":[199],"demonstrate":[200],"MPT-TISR":[202],"outperforms":[203],"existing":[204],"methods":[205],"terms":[207],"reconstructed":[209],"quality":[211],"significantly":[213],"improves":[214],"recognition":[216,222],"accuracy":[217],"downstream":[220],"task.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
