{"id":"https://openalex.org/W2614453579","doi":"https://doi.org/10.1109/icip.2017.8296476","title":"Wordfence: Text detection in natural images with border awareness","display_name":"Wordfence: Text detection in natural images with border awareness","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2614453579","doi":"https://doi.org/10.1109/icip.2017.8296476","mag":"2614453579"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5044289237","display_name":"Andrei Polzounov","orcid":null},"institutions":[{"id":"https://openalex.org/I9617848","display_name":"Universitat Polit\u00e8cnica de Catalunya","ror":"https://ror.org/03mb6wj31","country_code":"ES","type":"education","lineage":["https://openalex.org/I9617848"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Andrei Polzounov","raw_affiliation_strings":["Universtitat Polit\u00e8cnica da Catalunya"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universtitat Polit\u00e8cnica da Catalunya","institution_ids":["https://openalex.org/I9617848"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086843866","display_name":"Artsiom Ablavatski","orcid":null},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]},{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Artsiom Ablavatski","raw_affiliation_strings":["A*STAR Institute for Infocomm Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"A*STAR Institute for Infocomm Research","institution_ids":["https://openalex.org/I3005327000","https://openalex.org/I115228651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107873221","display_name":"Sergio Escalera","orcid":null},"institutions":[{"id":"https://openalex.org/I71999127","display_name":"Universitat de Barcelona","ror":"https://ror.org/021018s57","country_code":"ES","type":"education","lineage":["https://openalex.org/I71999127"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Sergio Escalera","raw_affiliation_strings":["Universitat de Barcelona and Computer Vision Center"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitat de Barcelona and Computer Vision Center","institution_ids":["https://openalex.org/I71999127"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023507910","display_name":"Shijian Lu","orcid":"https://orcid.org/0000-0002-6766-2506"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]},{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shijian Lu","raw_affiliation_strings":["A*STAR Institute for Infocomm Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"A*STAR Institute for Infocomm Research","institution_ids":["https://openalex.org/I3005327000","https://openalex.org/I115228651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100635804","display_name":"Jianfei Cai","orcid":"https://orcid.org/0000-0002-9444-3763"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jianfei Cai","raw_affiliation_strings":["Nanyang Technological University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3856,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.88739371,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"1","issue":null,"first_page":"1222","last_page":"1226"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9804999828338623,"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/softmax-function","display_name":"Softmax function","score":0.8063921928405762},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7997438311576843},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.7290588617324829},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7140563130378723},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6196951270103455},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6072003841400146},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.5880380868911743},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.5494623780250549},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5013010501861572},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.47156354784965515},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.46154338121414185},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.423710435628891},{"id":"https://openalex.org/keywords/word-recognition","display_name":"Word recognition","score":0.4102921783924103},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2854486107826233},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.11907520890235901},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06691503524780273}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8063921928405762},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7997438311576843},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.7290588617324829},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7140563130378723},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6196951270103455},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6072003841400146},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.5880380868911743},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.5494623780250549},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5013010501861572},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.47156354784965515},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.46154338121414185},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.423710435628891},{"id":"https://openalex.org/C150856459","wikidata":"https://www.wikidata.org/wiki/Q8034367","display_name":"Word recognition","level":3,"score":0.4102921783924103},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2854486107826233},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.11907520890235901},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06691503524780273},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1491389626","https://openalex.org/W1521064364","https://openalex.org/W1607307044","https://openalex.org/W1861492603","https://openalex.org/W1903029394","https://openalex.org/W1922126009","https://openalex.org/W1923697677","https://openalex.org/W1966693245","https://openalex.org/W1998042868","https://openalex.org/W2061802763","https://openalex.org/W2131447359","https://openalex.org/W2194187530","https://openalex.org/W2194775991","https://openalex.org/W2217433794","https://openalex.org/W2239285313","https://openalex.org/W2253806798","https://openalex.org/W2333563142","https://openalex.org/W2339589954","https://openalex.org/W2343052201","https://openalex.org/W2395360388","https://openalex.org/W2407521645","https://openalex.org/W2519818067","https://openalex.org/W2613718673","https://openalex.org/W2950800384","https://openalex.org/W2963037989","https://openalex.org/W2963542991","https://openalex.org/W2963840672","https://openalex.org/W3106250896","https://openalex.org/W4295246343","https://openalex.org/W6620707391","https://openalex.org/W6629368666","https://openalex.org/W6629590909","https://openalex.org/W6639102338","https://openalex.org/W6687615561","https://openalex.org/W6696085341","https://openalex.org/W6702842988","https://openalex.org/W6704491142","https://openalex.org/W6726857151","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2393940967","https://openalex.org/W2159591557","https://openalex.org/W2401522294","https://openalex.org/W2385598138","https://openalex.org/W2366925922","https://openalex.org/W1962828410","https://openalex.org/W2346578824","https://openalex.org/W2112534334","https://openalex.org/W2905950556","https://openalex.org/W2115592387"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"text":[3,78,100],"recognition":[4,16,142],"has":[5],"achieved":[6],"remarkable":[7],"success":[8],"in":[9,17,41],"recognizing":[10],"scanned":[11],"document":[12],"text.":[13],"However,":[14],"word":[15,39,63,84,102,114,141],"natural":[18],"images":[19,43],"is":[20,85],"still":[21],"an":[22,112],"open":[23],"problem,":[24],"which":[25,56,72],"generally":[26],"requires":[27],"time":[28],"consuming":[29],"post-processing":[30],"steps.":[31],"We":[32,117],"present":[33],"a":[34,65,94],"novel":[35,66],"architecture":[36],"for":[37],"individual":[38,62],"detection":[40,115],"scene":[42],"based":[44],"on":[45,122,129,136,148],"semantic":[46],"segmentation.":[47],"Our":[48],"contributions":[49],"are":[50],"twofold:":[51],"the":[52,89],"concept":[53],"of":[54],"WordFence,":[55],"detects":[57],"border":[58,103],"areas":[59],"surrounding":[60],"each":[61,83],"and":[64,75,88,101,131,133],"pixelwise":[67],"weighted":[68],"softmax":[69],"loss":[70,91],"function":[71,92],"penalizes":[73],"background":[74],"emphasizes":[76],"small":[77],"regions.":[79],"WordFence":[80],"ensures":[81],"that":[82],"detected":[86],"individually,":[87],"new":[90],"provides":[93],"strong":[95],"training":[96],"signal":[97],"to":[98],"both":[99],"localization.":[104],"The":[105],"proposed":[106],"technique":[107],"avoids":[108],"intensive":[109],"post-processing,":[110],"producing":[111],"end-to-end":[113,140],"system.":[116],"achieve":[118],"superior":[119],"localization":[120],"recall":[121,128,135],"common":[123],"benchmark":[124],"datasets":[125],"-":[126],"92%":[127],"ICDAR11":[130],"ICDAR13":[132],"63%":[134],"SVT.":[137],"Furthermore,":[138],"our":[139],"system":[143],"achieves":[144],"state-of-the-art":[145],"86%":[146],"F-Score":[147],"ICDAR13.":[149]},"counts_by_year":[{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
