{"id":"https://openalex.org/W3154876829","doi":null,"title":"Deep Learning-Based Text Detection and Recognition","display_name":"Deep Learning-Based Text Detection and Recognition","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3154876829","mag":"3154876829"},"language":"en","primary_location":{"id":"pmh:oai:opus.lib.uts.edu.au:10453/143893","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/143893","pdf_url":"http://hdl.handle.net/10453/143893","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10453/143893","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100446666","display_name":"Qingqing Wang","orcid":"https://orcid.org/0000-0003-0266-4452","observed_orcids":["https://orcid.org/0000-0003-0266-4452"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Qingqing Wang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-0266-4452","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5100446666"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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":0.0003000000142492354,"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/T10036","display_name":"Advanced Neural Network Applications","score":9.999999747378752e-05,"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/scene-text-detection","display_name":"scene text detection","score":0.9359999895095825},{"id":"https://openalex.org/keywords/scene-text-recognition","display_name":"scene text recognition","score":0.9629999995231628},{"id":"https://openalex.org/keywords/handwriting-recognition","display_name":"handwriting recognition","score":0.9520000219345093},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"semantic segmentation","score":0.8159999847412109},{"id":"https://openalex.org/keywords/convolutional-lstm","display_name":"convolutional LSTM","score":0.8569999933242798},{"id":"https://openalex.org/keywords/spatial-pyramid-pooling","display_name":"spatial pyramid pooling","score":0.9380000233650208},{"id":"https://openalex.org/keywords/xception","display_name":"Xception","score":0.6420000195503235},{"id":"https://openalex.org/keywords/mask-r-cnn","display_name":"Mask R-CNN","score":0.7289999723434448}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5282168388366699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5179587602615356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4898063838481903},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4082576334476471}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:opus.lib.uts.edu.au:10453/143893","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/143893","pdf_url":"http://hdl.handle.net/10453/143893","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},{"id":"mag:3154876829","doi":null,"is_oa":false,"landing_page_url":"https://opus.lib.uts.edu.au/bitstream/10453/143893/2/02whole.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:opus.lib.uts.edu.au:10453/143893","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/143893","pdf_url":"http://hdl.handle.net/10453/143893","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3154876829.pdf","grobid_xml":"https://content.openalex.org/works/W3154876829.grobid-xml"},"referenced_works_count":127,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W854541894","https://openalex.org/W1485009520","https://openalex.org/W1510835000","https://openalex.org/W1521044776","https://openalex.org/W1536680647","https://openalex.org/W1547848520","https://openalex.org/W1607307044","https://openalex.org/W1686810756","https://openalex.org/W1827297289","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W1922126009","https://openalex.org/W1923697677","https://openalex.org/W1972065312","https://openalex.org/W1985846974","https://openalex.org/W1998042868","https://openalex.org/W2000145530","https://openalex.org/W2001851755","https://openalex.org/W2001999290","https://openalex.org/W2004767896","https://openalex.org/W2005035880","https://openalex.org/W2012616030","https://openalex.org/W2022710553","https://openalex.org/W2023415694","https://openalex.org/W2030326191","https://openalex.org/W2031489346","https://openalex.org/W2049951199","https://openalex.org/W2056435187","https://openalex.org/W2056518953","https://openalex.org/W2061802763","https://openalex.org/W2064675550","https://openalex.org/W2069472161","https://openalex.org/W2080282572","https://openalex.org/W2103667008","https://openalex.org/W2108598243","https://openalex.org/W2109255472","https://openalex.org/W2109664771","https://openalex.org/W2110025586","https://openalex.org/W2112796928","https://openalex.org/W2122585011","https://openalex.org/W2124404372","https://openalex.org/W2127141656","https://openalex.org/W2135231474","https://openalex.org/W2140090592","https://openalex.org/W2142159465","https://openalex.org/W2144499799","https://openalex.org/W2145023731","https://openalex.org/W2148214126","https://openalex.org/W2152928267","https://openalex.org/W2167283987","https://openalex.org/W2170942820","https://openalex.org/W2183341477","https://openalex.org/W2194187530","https://openalex.org/W2294053032","https://openalex.org/W2336035754","https://openalex.org/W2339589954","https://openalex.org/W2396666837","https://openalex.org/W2412782625","https://openalex.org/W2464918637","https://openalex.org/W2504335775","https://openalex.org/W2515655118","https://openalex.org/W2519818067","https://openalex.org/W2550687635","https://openalex.org/W2565639579","https://openalex.org/W2577122925","https://openalex.org/W2578485521","https://openalex.org/W2587486463","https://openalex.org/W2593539516","https://openalex.org/W2595328592","https://openalex.org/W2601564443","https://openalex.org/W2604735854","https://openalex.org/W2605076167","https://openalex.org/W2606150549","https://openalex.org/W2630837129","https://openalex.org/W2725486421","https://openalex.org/W2740767790","https://openalex.org/W2740819638","https://openalex.org/W2741147179","https://openalex.org/W2741436143","https://openalex.org/W2747107070","https://openalex.org/W2750938222","https://openalex.org/W2751748110","https://openalex.org/W2754613063","https://openalex.org/W2766895242","https://openalex.org/W2772800855","https://openalex.org/W2776766448","https://openalex.org/W2785383245","https://openalex.org/W2786298913","https://openalex.org/W2788069964","https://openalex.org/W2788840914","https://openalex.org/W2793404167","https://openalex.org/W2795619303","https://openalex.org/W2803336464","https://openalex.org/W2803879696","https://openalex.org/W2806327167","https://openalex.org/W2810028092","https://openalex.org/W2831607544","https://openalex.org/W2875814315","https://openalex.org/W2891150346","https://openalex.org/W2891438060","https://openalex.org/W2901776468","https://openalex.org/W2906299545","https://openalex.org/W2922690896","https://openalex.org/W2939140832","https://openalex.org/W2949117887","https://openalex.org/W2950179405","https://openalex.org/W2962712200","https://openalex.org/W2962781062","https://openalex.org/W2962810613","https://openalex.org/W2963187132","https://openalex.org/W2963195262","https://openalex.org/W2963212638","https://openalex.org/W2963233387","https://openalex.org/W2963327605","https://openalex.org/W2963517393","https://openalex.org/W2963840241","https://openalex.org/W2963977642","https://openalex.org/W2964100062","https://openalex.org/W2964199361","https://openalex.org/W2964294787","https://openalex.org/W2964308564","https://openalex.org/W2965066169","https://openalex.org/W2984470164","https://openalex.org/W3004227653","https://openalex.org/W3082397598","https://openalex.org/W3106250896"],"related_works":["https://openalex.org/W6903884948","https://openalex.org/W3016156182","https://openalex.org/W2944248145","https://openalex.org/W2992238535","https://openalex.org/W4289756484","https://openalex.org/W7214620180","https://openalex.org/W7007948191","https://openalex.org/W2181660038","https://openalex.org/W2531341731","https://openalex.org/W7168387953"],"abstract_inverted_index":{"Texts":[0],"play":[1,160],"a":[2,146,267,275,368,376],"critical":[3],"role":[4],"in":[5,190,324],"our":[6],"daily":[7],"life.":[8],"They":[9],"are":[10,39,75,132,352],"everywhere":[11],"such":[12],"as":[13,44,177],"slogans":[14],"on":[15,19,167,173],"posters,":[16],"licence":[17],"plates":[18],"cars,":[20],"etc.,":[21],"to":[22,81,221,236,281,319,334,360,389],"transmit":[23],"information":[24,224,261,302],"and":[25,36,42,72,107,121,155,170,175,229,233,240,300,327,385],"knowledge.":[26],"With":[27],"the":[28,66,76,87,91,95,100,108,183,242,252,292,297,344],"popularity":[29],"of":[30,53,86,93,97,102,110,136,186,245,303,363],"mobile":[31],"devices":[32],"with":[33,218,337,348,397],"cameras,":[34],"more":[35,37],"texts":[38,49,71,74,80],"collected,":[40],"transmitted":[41],"stored":[43],"text":[45,103,117,122,127,138,168,188,192,200,227,269,305,311,371],"images.":[46],"Automatically":[47],"reading":[48],"from":[50,65,119],"images":[51],"is":[52,279],"high":[54],"application":[55],"potentials.":[56],"Therefore,":[57],"related":[58],"researches":[59,166],"have":[60,144],"been":[61],"attracting":[62],"considerable":[63],"attentions":[64],"computer":[67],"vision":[68],"community.":[69],"Scene":[70],"handwritten":[73,370],"two":[77,133,309],"most":[78],"difficult":[79],"be":[82],"automatically":[83],"read":[84],"because":[85],"challenges":[88],"posed":[89],"by":[90,285],"complexity":[92],"backgrounds,":[94],"uncertainty":[96],"capturing":[98],"conditions,":[99],"diversity":[101],"appearances,":[104],"touching":[105],"characters":[106],"variety":[109],"handwriting":[111],"styles.":[112],"\\nText":[113],"detection,":[114,193],"\ud835\udcbe.\ud835\udc52.,":[115,124],"localizing":[116],"areas":[118,128,189],"images,":[120,306],"recognition,":[123],"transcribing":[125],"located":[126],"into":[129,213,394],"character":[130],"sequences,":[131],"key":[134],"steps":[135],"robust":[137],"reading.":[139],"In":[140],"recent":[141],"years,":[142],"they":[143],"entered":[145],"deep":[147],"learning":[148],"era,":[149],"where":[150,274],"Convolutional":[151],"Neural":[152],"Network":[153],"(CNN)":[154],"Long":[156],"Short-Term":[157],"Memory":[158],"(LSTM)":[159],"important":[161],"roles.":[162],"Here,":[163],"we":[164,194,265,307,366],"conduct":[165],"detection":[169],"recognition":[171],"based":[172],"CNN":[174],"LSTM,":[176],"presented":[178],"below.":[179],"\\n1.":[180],"To":[181,250,290,342],"improve":[182],"recall":[184],"rate":[185],"small":[187,226],"oriented":[191],"propose":[195,266,308,367],"an":[196],"Xception-based":[197],"multi-ASPP-assembled":[198],"scene":[199,268,310],"detector":[201,270],"named":[202,271,313],"DeepText.":[203],"DeepText":[204],"inserts":[205],"multiple":[206],"Atrous":[207],"Spatial":[208,377],"Pyramid":[209,378],"Pooling":[210],"(ASPP)":[211],"modules":[212],"Xception":[214],"after":[215],"feature":[216,392,395],"maps":[217,393],"different":[219],"resolutions":[220],"retain":[222],"richer":[223],"for":[225,355],"areas,":[228],"introduces":[230],"auxiliary":[231,234],"connections":[232],"losses":[235],"speed":[237],"up":[238],"convergence":[239],"boost":[241],"discrimination":[243],"ability":[244],"lower":[246],"encoder":[247],"layers.":[248],"\\n2.":[249],"address":[251],"issue":[253],"that":[254,294,346],"Mask":[255],"R-CNN":[256],"cannot":[257],"fully":[258,349,386],"leverage":[259],"global":[260,276,287],"when":[262],"performing":[263],"predictions,":[264],"GMask":[272],"R-CNN,":[273],"mask":[277],"module":[278],"designed":[280],"perform":[282,321],"semantic":[283],"segmentation":[284],"considering":[286],"information.":[288,340],"\\n3.":[289],"tackle":[291],"problem":[293,345],"LSTM":[295,318],"neglects":[296],"valuable":[298],"spatial":[299,339],"structural":[301],"2-D":[304,325],"recognisers":[312],"FACLSTM,":[314],"which":[315,329],"exploits":[316],"convolution":[317],"directly":[320],"sequential":[322,356],"transcription":[323],"space,":[326],"ReELFA,":[328],"utilizes":[330],"one-hot":[331],"encoded":[332],"locations":[333],"enhance":[335],"features":[336],"pixels'":[338],"\\n4.":[341],"solve":[343],"CNNs":[347],"connected":[350,387],"layers":[351,384,388],"not":[353],"suitable":[354],"prediction":[357],"tasks":[358],"due":[359],"their":[361],"requirements":[362],"fixed-size":[364],"inputs/outputs,":[365],"CNN-based":[369],"recogniser":[372],"CFSPP.":[373],"CFSPP":[374],"embeds":[375],"Pooling-based":[379],"intermediate":[380],"layer":[381],"between":[382],"convolutional":[383],"convert":[390],"arbitrary-size":[391],"vectors":[396],"specific":[398],"lengths.":[399]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2021-04-26T00:00:00"}
