{"id":"https://openalex.org/W3090108697","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206949","title":"Low Resolution Handwritten Digit String Recognition based on Object Detection Network","display_name":"Low Resolution Handwritten Digit String Recognition based on Object Detection Network","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3090108697","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206949","mag":"3090108697"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5018891110","display_name":"Yingjie Xu","orcid":"https://orcid.org/0000-0003-0289-5525"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingjie Xu","raw_affiliation_strings":["School of Data Science and Engineering, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science and Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100419618","display_name":"Jun Guo","orcid":"https://orcid.org/0000-0002-6626-4135"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Guo","raw_affiliation_strings":["School of Data Science and Engineering, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science and Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9965000152587891,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9958999752998352,"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":0.7704980373382568},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.7642133235931396},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7101036310195923},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7074451446533203},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6732575297355652},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.656515896320343},{"id":"https://openalex.org/keywords/string","display_name":"String (physics)","score":0.6343462467193604},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.4685559868812561},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45717671513557434},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.45190635323524475},{"id":"https://openalex.org/keywords/digit-recognition","display_name":"Digit recognition","score":0.4249143600463867},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.42437681555747986},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4096333384513855},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1928231418132782},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11562824249267578}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7704980373382568},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.7642133235931396},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7101036310195923},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7074451446533203},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6732575297355652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.656515896320343},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.6343462467193604},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.4685559868812561},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45717671513557434},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.45190635323524475},{"id":"https://openalex.org/C2984784707","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Digit recognition","level":3,"score":0.4249143600463867},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.42437681555747986},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4096333384513855},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1928231418132782},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11562824249267578},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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":33,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1827297289","https://openalex.org/W1903029394","https://openalex.org/W2000145530","https://openalex.org/W2006582727","https://openalex.org/W2032487560","https://openalex.org/W2100921332","https://openalex.org/W2112796928","https://openalex.org/W2144506857","https://openalex.org/W2158957762","https://openalex.org/W2169304450","https://openalex.org/W2194187530","https://openalex.org/W2194775991","https://openalex.org/W2519818067","https://openalex.org/W2528751927","https://openalex.org/W2565639579","https://openalex.org/W2587231757","https://openalex.org/W2763095131","https://openalex.org/W2785333463","https://openalex.org/W2796347433","https://openalex.org/W2884561390","https://openalex.org/W2900752937","https://openalex.org/W2950136945","https://openalex.org/W2953301748","https://openalex.org/W2963351448","https://openalex.org/W2963959597","https://openalex.org/W4293584584","https://openalex.org/W6638685980","https://openalex.org/W6675313117","https://openalex.org/W6681406591","https://openalex.org/W6726857151","https://openalex.org/W6726983090","https://openalex.org/W6750227808"],"related_works":["https://openalex.org/W4311223090","https://openalex.org/W2804574147","https://openalex.org/W2756241593","https://openalex.org/W3195820617","https://openalex.org/W2935837427","https://openalex.org/W3175230847","https://openalex.org/W4293060694","https://openalex.org/W3113866414","https://openalex.org/W3011640627","https://openalex.org/W2801801420"],"abstract_inverted_index":{"A":[0],"novel":[1],"object":[2],"detection":[3],"network":[4,24,38],"is":[5,18,39],"proposed":[6],"in":[7],"this":[8],"paper":[9],"for":[10,31],"low":[11,47],"resolution":[12,48],"handwritten":[13],"digit":[14],"string":[15],"recognition.":[16,96],"It":[17],"composed":[19],"of":[20],"a":[21,69,74],"convolutional":[22],"neural":[23],"(CNN)":[25],"and":[26,33,54,76,81],"two":[27],"independent":[28],"output":[29],"branches":[30],"classification":[32],"bounding":[34],"box":[35],"regression.":[36],"The":[37,64],"designed":[40],"to":[41,60],"effectively":[42],"extract":[43],"the":[44,82],"features":[45],"from":[46],"images.":[49],"Non-categorized":[50],"non-maximum":[51],"suppression":[52],"(NMS)":[53],"mini-batch":[55],"fine-tuning":[56],"(MB-FT)":[57],"are":[58,66,85],"used":[59],"improve":[61],"accuracy":[62],"further.":[63],"experiments":[65],"conducted":[67],"on":[68],"new":[70],"dataset":[71],"collected":[72],"by":[73],"tablet":[75],"HDSRC":[77],"2014":[78],"benchmark":[79],"datasets,":[80],"high":[83],"metrics":[84],"obtained.":[86],"Furthermore,":[87],"its":[88],"prediction":[89],"speed":[90],"reaches":[91],"65":[92],"FPS":[93],"achieving":[94],"real-time":[95]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
