{"id":"https://openalex.org/W3163777876","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534319","title":"STRIDE: Scene Text Recognition In-Device","display_name":"STRIDE: Scene Text Recognition In-Device","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3163777876","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534319","mag":"3163777876"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534319","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534319","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2105.07795","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027398502","display_name":"Rachit S Munjal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Rachit S Munjal","raw_affiliation_strings":["On-Device AI, Samsung R&D Institute,Bangalore,India","On-Device AI, Samsung R&D Institute,Bangalore,India"],"affiliations":[{"raw_affiliation_string":"On-Device AI, Samsung R&D Institute,Bangalore,India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"On-Device AI, Samsung R&D Institute,Bangalore,India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025953920","display_name":"Arun D Prabhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arun D Prabhu","raw_affiliation_strings":["On-Device AI, Samsung R&D Institute,Bangalore,India","On-Device AI, Samsung R&D Institute,Bangalore,India"],"affiliations":[{"raw_affiliation_string":"On-Device AI, Samsung R&D Institute,Bangalore,India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"On-Device AI, Samsung R&D Institute,Bangalore,India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004204741","display_name":"Nikhil Arora","orcid":"https://orcid.org/0000-0002-3929-9316"},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nikhil Arora","raw_affiliation_strings":["On-Device AI, Samsung R&D Institute,Bangalore,India","On-Device AI, Samsung R&D Institute,Bangalore,India"],"affiliations":[{"raw_affiliation_string":"On-Device AI, Samsung R&D Institute,Bangalore,India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"On-Device AI, Samsung R&D Institute,Bangalore,India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045185756","display_name":"Sukumar Moharana","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sukumar Moharana","raw_affiliation_strings":["On-Device AI, Samsung R&D Institute,Bangalore,India","On-Device AI, Samsung R&D Institute,Bangalore,India"],"affiliations":[{"raw_affiliation_string":"On-Device AI, Samsung R&D Institute,Bangalore,India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"On-Device AI, Samsung R&D Institute,Bangalore,India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067079195","display_name":"Gopi Ramena","orcid":"https://orcid.org/0000-0002-7498-3973"},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Gopi Ramena","raw_affiliation_strings":["On-Device AI, Samsung R&D Institute,Bangalore,India","On-Device AI, Samsung R&D Institute,Bangalore,India"],"affiliations":[{"raw_affiliation_string":"On-Device AI, Samsung R&D Institute,Bangalore,India","institution_ids":["https://openalex.org/I4210139030"]},{"raw_affiliation_string":"On-Device AI, Samsung R&D Institute,Bangalore,India","institution_ids":["https://openalex.org/I4210139030"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5027398502"],"corresponding_institution_ids":["https://openalex.org/I4210139030"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05135021,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/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/T10036","display_name":"Advanced Neural Network Applications","score":0.9966999888420105,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9929999709129333,"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":0.831457257270813},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6342208385467529},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.613445520401001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6078702807426453},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"Optical character recognition","score":0.5367200970649719},{"id":"https://openalex.org/keywords/chipset","display_name":"Chipset","score":0.5254798531532288},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.479692667722702},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.426744282245636},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40345391631126404},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33523499965667725},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17948955297470093},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.16270390152931213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.831457257270813},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6342208385467529},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.613445520401001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6078702807426453},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.5367200970649719},{"id":"https://openalex.org/C73431340","wikidata":"https://www.wikidata.org/wiki/Q182656","display_name":"Chipset","level":3,"score":0.5254798531532288},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.479692667722702},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.426744282245636},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40345391631126404},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33523499965667725},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17948955297470093},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.16270390152931213},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534319","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534319","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2105.07795","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.07795","pdf_url":"https://arxiv.org/pdf/2105.07795","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3163777876","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2105.07795","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2105.07795","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2105.07795","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2105.07795","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.07795","pdf_url":"https://arxiv.org/pdf/2105.07795","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1491389626","https://openalex.org/W1522301498","https://openalex.org/W1607307044","https://openalex.org/W1686810756","https://openalex.org/W1981283549","https://openalex.org/W1998042868","https://openalex.org/W2008806374","https://openalex.org/W2122221966","https://openalex.org/W2127141656","https://openalex.org/W2144554289","https://openalex.org/W2194187530","https://openalex.org/W2194775991","https://openalex.org/W2293634267","https://openalex.org/W2294053032","https://openalex.org/W2343052201","https://openalex.org/W2593572697","https://openalex.org/W2609829154","https://openalex.org/W2740767790","https://openalex.org/W2750938222","https://openalex.org/W2752782242","https://openalex.org/W2785383245","https://openalex.org/W2795619303","https://openalex.org/W2809273748","https://openalex.org/W2810983211","https://openalex.org/W2927058921","https://openalex.org/W2949586622","https://openalex.org/W2951559372","https://openalex.org/W2952302849","https://openalex.org/W2952439627","https://openalex.org/W2963420686","https://openalex.org/W2963517393","https://openalex.org/W2963918968","https://openalex.org/W2965066169","https://openalex.org/W3004846386","https://openalex.org/W3021481629","https://openalex.org/W3087858202","https://openalex.org/W3109202259","https://openalex.org/W3156660616","https://openalex.org/W6629590909","https://openalex.org/W6631190155","https://openalex.org/W6636382570","https://openalex.org/W6637373629","https://openalex.org/W6713134421","https://openalex.org/W6753412334","https://openalex.org/W6757161006","https://openalex.org/W6776488277","https://openalex.org/W6783441721","https://openalex.org/W6786086243"],"related_works":["https://openalex.org/W3003552100","https://openalex.org/W3198848843","https://openalex.org/W3199161515","https://openalex.org/W3133366284","https://openalex.org/W3199928321","https://openalex.org/W2800748770","https://openalex.org/W2028252982","https://openalex.org/W3200351427","https://openalex.org/W3129452381","https://openalex.org/W1812096077","https://openalex.org/W2135746064","https://openalex.org/W2895275282","https://openalex.org/W3048860274","https://openalex.org/W3187989292","https://openalex.org/W2884815186","https://openalex.org/W3136542657","https://openalex.org/W3005226210","https://openalex.org/W3015155198","https://openalex.org/W3196904463","https://openalex.org/W2971553110"],"abstract_inverted_index":{"Optical":[0],"Character":[1],"Recognition":[2],"(OCR)":[3],"systems":[4],"have":[5],"been":[6],"widely":[7],"used":[8],"in":[9],"various":[10],"applications":[11],"for":[12,85],"extracting":[13],"semantic":[14],"information":[15,110],"from":[16],"images.":[17],"To":[18],"give":[19],"the":[20,36,73,91,98,112,143,171,181,194],"user":[21],"more":[22],"control":[23],"over":[24],"their":[25],"privacy,":[26],"an":[27,50,185,201],"on-device":[28,156,183],"solution":[29],"is":[30],"needed.":[31],"The":[32,152],"current":[33],"state":[34],"of":[35,75,93,146,158,188,203],"art":[37],"models":[38],"are":[39,79],"too":[40],"heavy":[41],"and":[42,63,82,107,149,161,164,174,199],"complex":[43],"to":[44,71,97,104,111,141,170],"be":[45],"deployed":[46],"on-device.":[47],"We":[48,133,179],"develop":[49],"efficient":[51],"lightweight":[52],"scene":[53],"text":[54,66,99],"recognition":[55,100,145],"(STR)":[56],"system,":[57],"which":[58,102],"has":[59],"only":[60],"0.88M":[61],"parameters":[62],"performs":[64],"real-time":[65],"recognition.":[67],"Attention":[68],"modules":[69,96],"tend":[70],"boost":[72],"accuracy":[74,125,167,202],"STR":[76],"networks":[77],"but":[78],"generally":[80],"slow":[81],"not":[83],"optimized":[84],"device":[86,198],"inference.":[87],"So,":[88],"we":[89],"propose":[90],"use":[92],"convolution":[94],"attention":[95,109],"networks,":[101],"aims":[103],"provide":[105],"channel":[106],"spatial":[108],"LSTM":[113],"module":[114],"by":[115,130],"adding":[116],"very":[117],"minimal":[118],"computational":[119],"cost.":[120],"It":[121],"boosts":[122],"our":[123],"word":[124,192],"on":[126,193,205],"ICDAR":[127],"13":[128],"dataset":[129],"almost":[131],"2%.":[132],"also":[134],"introduce":[135],"a":[136],"novel":[137],"orientation":[138],"classifier":[139],"module,":[140],"support":[142],"simultaneous":[144],"both":[147],"horizontal":[148],"vertical":[150],"text.":[151],"proposed":[153],"model":[154],"surpasses":[155],"metrics":[157],"inference":[159,186],"time":[160],"memory":[162],"footprint":[163],"achieves":[165],"comparable":[166],"when":[168],"compared":[169],"leading":[172],"commercial":[173],"other":[175],"open-source":[176],"OCR":[177],"engines.":[178],"deploy":[180],"system":[182],"with":[184],"speed":[187],"2.44":[189],"ms":[190],"per":[191],"Exynos":[195],"990":[196],"chipset":[197],"achieve":[200],"88.4%":[204],"ICDAR-13":[206],"dataset.":[207]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}