{"id":"https://openalex.org/W4386180224","doi":"https://doi.org/10.1109/tits.2023.3305686","title":"HFENet: Hybrid Feature Enhancement Network for Detecting Texts in Scenes and Traffic Panels","display_name":"HFENet: Hybrid Feature Enhancement Network for Detecting Texts in Scenes and Traffic Panels","publication_year":2023,"publication_date":"2023-08-25","ids":{"openalex":"https://openalex.org/W4386180224","doi":"https://doi.org/10.1109/tits.2023.3305686"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2023.3305686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3305686","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation 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/A5048076905","display_name":"Min Liang","orcid":"https://orcid.org/0000-0003-4749-7635"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Min Liang","raw_affiliation_strings":["Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4749-7635","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078514263","display_name":"Xiaobin Zhu","orcid":"https://orcid.org/0000-0003-2702-4136"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobin Zhu","raw_affiliation_strings":["Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2702-4136","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040880250","display_name":"Hongyang Zhou","orcid":"https://orcid.org/0000-0002-4705-9304"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyang Zhou","raw_affiliation_strings":["Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072850755","display_name":"Jingyan Qin","orcid":"https://orcid.org/0000-0002-4101-4316"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyan Qin","raw_affiliation_strings":["Department of Industrial Design, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Design, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074514262","display_name":"Xu-Cheng Yin","orcid":"https://orcid.org/0000-0003-0023-0220"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu-Cheng Yin","raw_affiliation_strings":["Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0023-0220","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5048076905"],"corresponding_institution_ids":["https://openalex.org/I92403157"],"apc_list":null,"apc_paid":null,"fwci":1.0597,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.79364934,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"24","issue":"12","first_page":"14200","last_page":"14212"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","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/T10601","display_name":"Handwritten Text Recognition Techniques","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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9790999889373779,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7427997589111328},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7154717445373535},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.690597414970398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6114152669906616},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5818442702293396},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5256539583206177},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4667670428752899},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32706373929977417}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7427997589111328},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7154717445373535},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.690597414970398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6114152669906616},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5818442702293396},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5256539583206177},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4667670428752899},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32706373929977417},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2023.3305686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3305686","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6800000071525574}],"awards":[{"id":"https://openalex.org/G2141617675","display_name":null,"funder_award_id":"62076024","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2903026367","display_name":null,"funder_award_id":"62172035","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G356227064","display_name":null,"funder_award_id":"62006018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4738090328","display_name":null,"funder_award_id":"61806017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8772010899","display_name":null,"funder_award_id":"62125601","funder_id":"https://openalex.org/F4320336125","funder_display_name":"National Science Fund for Distinguished Young Scholars"},{"id":"https://openalex.org/G8879444097","display_name":null,"funder_award_id":"2020AAA0109700","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320336125","display_name":"National Science Fund for Distinguished Young Scholars","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":75,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1972065312","https://openalex.org/W1988461287","https://openalex.org/W2008806374","https://openalex.org/W2144554289","https://openalex.org/W2194775991","https://openalex.org/W2343052201","https://openalex.org/W2519321174","https://openalex.org/W2519818067","https://openalex.org/W2550687635","https://openalex.org/W2565639579","https://openalex.org/W2593539516","https://openalex.org/W2601564443","https://openalex.org/W2605076167","https://openalex.org/W2605982830","https://openalex.org/W2752782242","https://openalex.org/W2779757316","https://openalex.org/W2784050770","https://openalex.org/W2785383245","https://openalex.org/W2810028092","https://openalex.org/W2888728082","https://openalex.org/W2914492226","https://openalex.org/W2953606406","https://openalex.org/W2962810613","https://openalex.org/W2963068450","https://openalex.org/W2963353821","https://openalex.org/W2963647456","https://openalex.org/W2964685115","https://openalex.org/W2965463054","https://openalex.org/W2966926453","https://openalex.org/W2972424968","https://openalex.org/W2982121427","https://openalex.org/W2982769033","https://openalex.org/W2991626090","https://openalex.org/W2996411315","https://openalex.org/W2998621280","https://openalex.org/W3003312382","https://openalex.org/W3018757597","https://openalex.org/W3024377038","https://openalex.org/W3034390599","https://openalex.org/W3034514377","https://openalex.org/W3034971973","https://openalex.org/W3035028692","https://openalex.org/W3035222584","https://openalex.org/W3035679705","https://openalex.org/W3043531819","https://openalex.org/W3083321694","https://openalex.org/W3093861118","https://openalex.org/W3096609285","https://openalex.org/W3102695566","https://openalex.org/W3103667010","https://openalex.org/W3106228955","https://openalex.org/W3116963012","https://openalex.org/W3172799005","https://openalex.org/W3180134609","https://openalex.org/W3181016597","https://openalex.org/W3184364189","https://openalex.org/W3184923351","https://openalex.org/W3185722123","https://openalex.org/W3186906052","https://openalex.org/W3205961173","https://openalex.org/W3206615376","https://openalex.org/W3207420819","https://openalex.org/W3211269695","https://openalex.org/W4214922754","https://openalex.org/W4225787349","https://openalex.org/W4280527491","https://openalex.org/W4281250886","https://openalex.org/W4289752563","https://openalex.org/W4293584584","https://openalex.org/W4312593844","https://openalex.org/W6620707391","https://openalex.org/W6750227808","https://openalex.org/W6767563286","https://openalex.org/W6947681574"],"related_works":["https://openalex.org/W3119773509","https://openalex.org/W2905271011","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W2619127353","https://openalex.org/W3164948662","https://openalex.org/W4289536128","https://openalex.org/W3153597579"],"abstract_inverted_index":{"Text":[0],"detection":[1,16],"in":[2,40,83,159],"complex":[3],"scene":[4,14],"images":[5],"is":[6,117],"a":[7,93,147],"challenging":[8],"task":[9],"for":[10,29,56,80,102,142,165],"intelligent":[11],"transportation.":[12],"Existing":[13],"text":[15,57,143],"methods":[17],"often":[18],"adopt":[19],"multi-scale":[20,41],"feature":[21,27,42,98,105,157],"learning":[22],"strategies":[23],"to":[24,72,107,133,153],"extract":[25],"informative":[26],"representations":[28,106,158],"covering":[30],"objects":[31],"of":[32,77,138,162,193],"various":[33],"sizes.":[34],"However,":[35],"the":[36,75,134,160,190],"sampling":[37],"operation":[38],"inherent":[39],"generation":[43],"can":[44],"easily":[45],"impair":[46],"high-frequency":[47,78,111],"details":[48],"(e.g.,":[49],"textures":[50],"and":[51,85,110,119,136,187],"boundaries),":[52],"which":[53],"are":[54],"critical":[55],"detection.":[58],"In":[59,130],"this":[60],"work,":[61],"we":[62,91,145],"propose":[63,92,146],"an":[64],"innovative":[65],"Hybrid":[66],"Feature":[67],"Enhancement":[68],"Network":[69],"(dubbed":[70],"HFENet)":[71],"explicitly":[73,154],"improve":[74],"quality":[76],"information":[79],"detecting":[81],"texts":[82],"scenes":[84],"traffic":[86],"panels.":[87],"To":[88],"be":[89,121],"concrete,":[90],"simple":[94],"yet":[95],"effective":[96],"self-guided":[97],"enhancement":[99,150],"module":[100,151],"(SFEM)":[101],"globally":[103],"lifting":[104],"highly":[108],"discriminative":[109],"abundant":[112],"ones.":[113],"Notably,":[114],"our":[115,194],"SFEM":[116],"pluggable":[118],"will":[120],"removed":[122],"after":[123],"training":[124],"without":[125],"introducing":[126],"extra":[127],"computational":[128],"costs.":[129],"addition,":[131],"due":[132],"challenge":[135],"importance":[137],"accurately":[139],"predicting":[140],"boundaries":[141],"detection,":[144],"novel":[148],"boundary":[149,163],"(BEM)":[152],"strengthen":[155],"local":[156],"guidance":[161],"annotation":[164],"accurate":[166],"localization.":[167],"Extensive":[168],"experiments":[169],"on":[170],"multiple":[171],"publicly":[172],"available":[173],"datasets":[174],"(i.e.,":[175],"MSRA-TD500,":[176],"CTW1500,":[177],"Total-Text,":[178],"Traffic":[179],"Guide":[180],"Panel":[181],"Dataset,":[182,186],"Chinese":[183],"Road":[184],"Plate":[185],"ASAYAR_TXT)":[188],"verify":[189],"state-of-the-art":[191],"performance":[192],"method.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}