{"id":"https://openalex.org/W3175715177","doi":"https://doi.org/10.1109/icccsp52374.2021.9465515","title":"Design of a Light-weight Natural Scene Text Detection System","display_name":"Design of a Light-weight Natural Scene Text Detection System","publication_year":2021,"publication_date":"2021-05-24","ids":{"openalex":"https://openalex.org/W3175715177","doi":"https://doi.org/10.1109/icccsp52374.2021.9465515","mag":"3175715177"},"language":"en","primary_location":{"id":"doi:10.1109/icccsp52374.2021.9465515","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccsp52374.2021.9465515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Computer, Communication and Signal Processing (ICCCSP)","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/A5010502527","display_name":"Jyoti Ghosh","orcid":"https://orcid.org/0000-0003-3300-9442"},"institutions":[{"id":"https://openalex.org/I138537684","display_name":"Gauhati University","ror":"https://ror.org/01ppj9r51","country_code":"IN","type":"education","lineage":["https://openalex.org/I138537684"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Jyoti Ghosh","raw_affiliation_strings":["Gauhati University, Guwahati, Assam, India"],"affiliations":[{"raw_affiliation_string":"Gauhati University, Guwahati, Assam, India","institution_ids":["https://openalex.org/I138537684"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019060005","display_name":"Anjan Kumar Talukdar","orcid":"https://orcid.org/0000-0001-8547-4595"},"institutions":[{"id":"https://openalex.org/I138537684","display_name":"Gauhati University","ror":"https://ror.org/01ppj9r51","country_code":"IN","type":"education","lineage":["https://openalex.org/I138537684"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anjan Kumar Talukdar","raw_affiliation_strings":["Gauhati University, Guwahati, Assam, India"],"affiliations":[{"raw_affiliation_string":"Gauhati University, Guwahati, Assam, India","institution_ids":["https://openalex.org/I138537684"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025157529","display_name":"Kandarpa Kumar Sarma","orcid":"https://orcid.org/0000-0002-6236-0461"},"institutions":[{"id":"https://openalex.org/I138537684","display_name":"Gauhati University","ror":"https://ror.org/01ppj9r51","country_code":"IN","type":"education","lineage":["https://openalex.org/I138537684"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kandarpa Kumar Sarma","raw_affiliation_strings":["Gauhati University, Guwahati, Assam, India"],"affiliations":[{"raw_affiliation_string":"Gauhati University, Guwahati, Assam, India","institution_ids":["https://openalex.org/I138537684"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010502527"],"corresponding_institution_ids":["https://openalex.org/I138537684"],"apc_list":null,"apc_paid":null,"fwci":0.0961,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.37377451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"34","issue":null,"first_page":"221","last_page":"227"},"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9932000041007996,"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":0.9930999875068665,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8448962569236755},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.698620080947876},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6825135946273804},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6006036400794983},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.553214430809021},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5372720956802368},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.44884192943573},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4440065026283264},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.42790722846984863},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.42365899682044983},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3774707615375519},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3202272951602936}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8448962569236755},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.698620080947876},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6825135946273804},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6006036400794983},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.553214430809021},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5372720956802368},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.44884192943573},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4440065026283264},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.42790722846984863},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.42365899682044983},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3774707615375519},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3202272951602936},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccsp52374.2021.9465515","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccsp52374.2021.9465515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Computer, Communication and Signal Processing (ICCCSP)","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":38,"referenced_works":["https://openalex.org/W1934428292","https://openalex.org/W1971822075","https://openalex.org/W1998042868","https://openalex.org/W2008806374","https://openalex.org/W2011301426","https://openalex.org/W2204328893","https://openalex.org/W2242464395","https://openalex.org/W2342249984","https://openalex.org/W2472803348","https://openalex.org/W2550687635","https://openalex.org/W2606911419","https://openalex.org/W2810028092","https://openalex.org/W2831607544","https://openalex.org/W2903260224","https://openalex.org/W2922690896","https://openalex.org/W2945048248","https://openalex.org/W2962773189","https://openalex.org/W2962810613","https://openalex.org/W2963163009","https://openalex.org/W2963299604","https://openalex.org/W2963398399","https://openalex.org/W2963647456","https://openalex.org/W2967155990","https://openalex.org/W2967615747","https://openalex.org/W2970930436","https://openalex.org/W2991626090","https://openalex.org/W2998621280","https://openalex.org/W3012458836","https://openalex.org/W3035222584","https://openalex.org/W3035965352","https://openalex.org/W3082397598","https://openalex.org/W3099878876","https://openalex.org/W3101769104","https://openalex.org/W3108524627","https://openalex.org/W3159674028","https://openalex.org/W3210232381","https://openalex.org/W6760673939","https://openalex.org/W6803376173"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4390846322"],"abstract_inverted_index":{"Scene":[0],"Text":[1],"Detection":[2],"is":[3,104,117,124],"one":[4],"of":[5,9,20,44,69,88,109,148,179,187,194,198],"the":[6,18,48,58,67,70,86,107,113,120,132,135,141,177,180,185,189,199,210],"vast":[7],"tasks":[8],"computer":[10],"vision":[11],"that":[12,209],"have":[13,27],"received":[14],"immense":[15],"progress":[16],"in":[17,80,93,106,161,172,217],"field":[19],"deep":[21],"learning":[22],"(DL).":[23],"Several":[24],"DL":[25],"models":[26,56,95],"been":[28],"made":[29,105,125],"with":[30,40,82,134,151,164],"large":[31],"scale":[32],"neural":[33],"network":[34],"structures":[35],"and":[36,72,98,168,182,204],"heavy":[37],"weight":[38,146],"files":[39],"a":[41,61,145,214],"huge":[42],"number":[43],"parameters":[45],"to":[46,60,77],"increase":[47],"natural":[49,221],"scene":[50,222],"text":[51],"detection":[52],"performance.":[53],"Although":[54],"these":[55],"improve":[57],"performance":[59,197,216],"high":[62],"range,":[63],"but":[64],"they":[65],"reduces":[66],"speed":[68,178],"model":[71,103,143,157,181,201],"it":[73],"also":[74],"becomes":[75],"difficult":[76],"use":[78],"them":[79],"platforms":[81],"limited":[83],"resources.":[84],"Therefore,":[85],"goal":[87],"our":[89],"proposed":[90,102,142,156,190,200,211],"work":[91,191,212],"lies":[92],"making":[94,188],"smaller,":[96],"faster":[97],"more":[99],"efficient.":[100],"Our":[101],"form":[108],"encoder-decoder":[110],"architecture":[111],"where":[112],"light-weight":[114],"model,":[115],"MobileNetV2":[116],"used":[118],"as":[119],"encoder.":[121],"The":[122,155,196],"decoder":[123],"by":[126],"concatenating":[127],"certain":[128],"feature":[129],"maps":[130],"from":[131,220],"encoder":[133],"transposed":[136],"convolutional":[137],"layers.":[138],"After":[139],"training,":[140],"generates":[144],"file":[147],"4":[149],"MB":[150],"1.1":[152],"M":[153],"parameters.":[154],"can":[158],"be":[159],"trained":[160],"Google":[162],"Colaboratory":[163],"12":[165],"GB":[166],"RAM":[167],"without":[169],"using":[170],"GPU":[171],"few":[173],"hours":[174],"which":[175,183],"shows":[176,208],"gives":[184],"advantage":[186],"at":[192],"free":[193],"cost.":[195],"on":[202],"Total-Text":[203],"ICDAR":[205],"2013":[206],"datasets":[207],"achieves":[213],"desirable":[215],"detecting":[218],"texts":[219],"images.":[223]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}