{"id":"https://openalex.org/W2903134060","doi":"https://doi.org/10.1109/icpr.2018.8545022","title":"Focus on Scene Text Using Deep Reinforcement Learning","display_name":"Focus on Scene Text Using Deep Reinforcement Learning","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2903134060","doi":"https://doi.org/10.1109/icpr.2018.8545022","mag":"2903134060"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5069496806","display_name":"Haobin Wang","orcid":"https://orcid.org/0000-0002-2003-131X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haobin Wang","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology * Corresponding author"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology * Corresponding author","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101528918","display_name":"Shuangping Huang","orcid":"https://orcid.org/0000-0002-5544-4544"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangping Huang","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology * Corresponding author"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology * Corresponding author","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080674767","display_name":"Lianwen Jin","orcid":"https://orcid.org/0000-0002-5456-0957"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianwen Jin","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology * Corresponding author"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology * Corresponding author","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5069496806"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.2089,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.56978486,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"529","issue":null,"first_page":"3759","last_page":"3765"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","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/T10601","display_name":"Handwritten Text Recognition Techniques","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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9904999732971191,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9865000247955322,"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/bounding-overwatch","display_name":"Bounding overwatch","score":0.8487669825553894},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7889586687088013},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7722580432891846},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.7472034692764282},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6688405275344849},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.648769736289978},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5779715776443481},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4415076971054077},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.4404720962047577},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4279329180717468},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.351991206407547},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09503349661827087}],"concepts":[{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.8487669825553894},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7889586687088013},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7722580432891846},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.7472034692764282},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6688405275344849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.648769736289978},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5779715776443481},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4415076971054077},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.4404720962047577},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4279329180717468},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.351991206407547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09503349661827087},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W70975097","https://openalex.org/W639708223","https://openalex.org/W1488125194","https://openalex.org/W1521064364","https://openalex.org/W1522301498","https://openalex.org/W1539258218","https://openalex.org/W1686810756","https://openalex.org/W1771410628","https://openalex.org/W1935817682","https://openalex.org/W1964883574","https://openalex.org/W1968234316","https://openalex.org/W2006408850","https://openalex.org/W2008806374","https://openalex.org/W2025576683","https://openalex.org/W2038533067","https://openalex.org/W2069472161","https://openalex.org/W2117539524","https://openalex.org/W2117586922","https://openalex.org/W2121839820","https://openalex.org/W2128854450","https://openalex.org/W2137718414","https://openalex.org/W2138326121","https://openalex.org/W2145339207","https://openalex.org/W2146472835","https://openalex.org/W2158710217","https://openalex.org/W2165401735","https://openalex.org/W2179488730","https://openalex.org/W2204328893","https://openalex.org/W2239285313","https://openalex.org/W2257979135","https://openalex.org/W2291772168","https://openalex.org/W2395360388","https://openalex.org/W2550687635","https://openalex.org/W2601066903","https://openalex.org/W2604243686","https://openalex.org/W2613718673","https://openalex.org/W2739678353","https://openalex.org/W2766447205","https://openalex.org/W2949191055","https://openalex.org/W2949267040","https://openalex.org/W2950872548","https://openalex.org/W2962773189","https://openalex.org/W2962935569","https://openalex.org/W2963262099","https://openalex.org/W2963836589","https://openalex.org/W2963977642","https://openalex.org/W2964121744","https://openalex.org/W3106250896","https://openalex.org/W6602936574","https://openalex.org/W6620707391","https://openalex.org/W6629021407","https://openalex.org/W6631165897","https://openalex.org/W6632178270","https://openalex.org/W6638018090","https://openalex.org/W6681725914","https://openalex.org/W6697063336","https://openalex.org/W6703271639","https://openalex.org/W6729791593","https://openalex.org/W6735544697","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W4287027631","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"Scene":[0],"text":[1,26,40,93,107,134],"detection":[2],"has":[3,17],"been":[4,18,28],"attracting":[5],"increasing":[6],"interests":[7],"in":[8,70,129],"recent":[9],"years":[10],"and":[11,62,82,135,161,182],"a":[12,52,77,101,178,183,204],"rich":[13],"body":[14],"of":[15,23,46,54,64,80,88,91,158,172],"approaches":[16],"proposed.":[19],"These":[20],"previous":[21],"works":[22],"detecting":[24],"scene":[25,106,167,173],"have":[27],"dominated":[29],"by":[30,110,147],"region":[31,127,140,209],"proposals":[32,141,210],"based":[33],"approaches,":[34],"which":[35],"always":[36],"generate":[37],"too":[38],"many":[39],"candidates":[41,56],"relative":[42],"to":[43,119,151,154,165],"the":[44,65,86,97,121,125,139,170,194,200,214],"number":[45],"ground":[47,215],"truth":[48,216],"bounding":[49,217],"boxes.":[50,218],"Only":[51],"few":[53,212],"those":[55],"are":[57],"output":[58],"as":[59,124,211,213],"true":[60],"predictions,":[61],"most":[63],"other":[66],"is":[67,145],"fruitlessly":[68],"involved":[69],"regression":[71],"or":[72],"classification":[73],"predictions":[74],"that":[75,199],"consume":[76],"great":[78],"amount":[79],"time":[81],"storage.":[83],"Thus":[84],"emerges":[85],"problem":[87],"low":[89],"efficiency":[90],"generating":[92],"candidates.":[94],"To":[95],"address":[96],"issue,":[98],"we":[99,175],"propose":[100,177],"method":[102,202],"for":[103],"focusing":[104],"on":[105,193],"gradually":[108],"guided":[109],"an":[111,117],"active":[112],"model.":[113],"The":[114,143,191],"model":[115],"allows":[116],"agent":[118,144],"take":[120],"whole":[122],"image":[123],"only":[126],"proposal":[128],"each":[130],"episode":[131],"when":[132],"locating":[133],"therefore":[136],"significantly":[137],"reduces":[138],"needed.":[142],"trained":[146],"deep":[148],"reinforcement":[149],"strategy":[150],"learn":[152],"how":[153],"estimate":[155],"future":[156],"returns":[157],"given":[159],"states":[160],"sequentially":[162],"make":[163],"decisions":[164],"find":[166],"text.":[168],"Considering":[169],"characteristics":[171],"text,":[174],"additionally":[176],"flexible":[179],"action":[180],"scheme":[181,186],"new":[184],"reward":[185],"together":[187],"with":[188],"lazy":[189],"punishment.":[190],"experiments":[192],"ICDAR":[195],"2013":[196],"dataset":[197],"shows":[198],"proposed":[201],"achieve":[203],"promising":[205],"performance":[206],"while":[207],"using":[208]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}