{"id":"https://openalex.org/W2897758350","doi":"https://doi.org/10.1109/ijcnn.2018.8489318","title":"Deep CNNs with Rotational Filters for Rotation Invariant Character Recognition","display_name":"Deep CNNs with Rotational Filters for Rotation Invariant Character Recognition","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2897758350","doi":"https://doi.org/10.1109/ijcnn.2018.8489318","mag":"2897758350"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2018.8489318","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","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/A5001877403","display_name":"Erik Barrow","orcid":null},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Erik Barrow","raw_affiliation_strings":["School of Computing, Electronics, and Mathematics, Coventry University, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing, Electronics, and Mathematics, Coventry University, UK","institution_ids":["https://openalex.org/I73417466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030706452","display_name":"Mark Eastwood","orcid":"https://orcid.org/0000-0003-3768-7953"},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mark Eastwood","raw_affiliation_strings":["School of Computing, Electronics, and Mathematics, Coventry University, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing, Electronics, and Mathematics, Coventry University, UK","institution_ids":["https://openalex.org/I73417466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016214321","display_name":"Chrisina Jayne","orcid":"https://orcid.org/0000-0001-7292-2109"},"institutions":[{"id":"https://openalex.org/I124261462","display_name":"Oxford Brookes University","ror":"https://ror.org/04v2twj65","country_code":"GB","type":"education","lineage":["https://openalex.org/I124261462"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chrisina Jayne","raw_affiliation_strings":["Oxford Brookes University, UK"],"affiliations":[{"raw_affiliation_string":"Oxford Brookes University, UK","institution_ids":["https://openalex.org/I124261462"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5001877403"],"corresponding_institution_ids":["https://openalex.org/I73417466"],"apc_list":null,"apc_paid":null,"fwci":0.1064,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46888933,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9980999827384949,"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/mnist-database","display_name":"MNIST database","score":0.9632326364517212},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.7374197244644165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7105326056480408},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6864749193191528},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6656656861305237},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6303632259368896},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5754905939102173},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5711385607719421},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.5539014339447021},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.5317277908325195},{"id":"https://openalex.org/keywords/character-recognition","display_name":"Character recognition","score":0.4943273067474365},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.38672614097595215},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35185831785202026},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33344894647598267},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2912524938583374},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0757274329662323}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.9632326364517212},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.7374197244644165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7105326056480408},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6864749193191528},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6656656861305237},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6303632259368896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5754905939102173},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5711385607719421},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.5539014339447021},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.5317277908325195},{"id":"https://openalex.org/C2987247673","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Character recognition","level":3,"score":0.4943273067474365},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.38672614097595215},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35185831785202026},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33344894647598267},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2912524938583374},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0757274329662323},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2018.8489318","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:https://research.tees.ac.uk/ws/oai:openaire_cris_publications/2c417bfc-89de-4332-abe0-6fa605674549","is_oa":false,"landing_page_url":"https://research.tees.ac.uk/en/publications/2c417bfc-89de-4332-abe0-6fa605674549","pdf_url":null,"source":{"id":"https://openalex.org/S4306401198","display_name":"TeesRep (Teesside University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I874055015","host_organization_name":"Teesside University","host_organization_lineage":["https://openalex.org/I874055015"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Barrow, E, Eastwood, M & Jayne, C 2018, Deep CNNs with Rotational Filters for Rotation Invariant Character Recognition. in 2018 International Joint Conference on Neural Networks (IJCNN) Proceedings. International Joint Conference on Neural Networks (IJCNN), vol. 2018, IEEE, 2018 International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, 8/07/18. https://doi.org/10.1109/IJCNN.2018.8489318","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1579279110","https://openalex.org/W1836465849","https://openalex.org/W2005750530","https://openalex.org/W2038864232","https://openalex.org/W2044738244","https://openalex.org/W2112193291","https://openalex.org/W2112796928","https://openalex.org/W2116248957","https://openalex.org/W2124386111","https://openalex.org/W2155893237","https://openalex.org/W2344005843","https://openalex.org/W2437181147","https://openalex.org/W2949117887","https://openalex.org/W3102779874","https://openalex.org/W4213116910","https://openalex.org/W6638667902","https://openalex.org/W6677603168"],"related_works":["https://openalex.org/W2950475743","https://openalex.org/W4386603768","https://openalex.org/W2886711096","https://openalex.org/W4380078352","https://openalex.org/W3046591097","https://openalex.org/W2590796488","https://openalex.org/W2139834217","https://openalex.org/W2100099236","https://openalex.org/W1575585820","https://openalex.org/W2103090617"],"abstract_inverted_index":{"This":[0,103],"paper":[1,104],"explores":[2],"the":[3,35,52,69,72,91,100,111],"use":[4,114],"of":[5,8,34,63,110],"parallel":[6,60],"columns":[7,36],"convolutional":[9,30],"layers":[10],"with":[11,51,55,84,115],"tied":[12],"weights":[13],"presented":[14],"to":[15,24,46,68],"each":[16],"column":[17],"in":[18,88],"a":[19,26,40,85,95,107],"layer":[20],"at":[21],"different":[22],"rotations,":[23],"create":[25],"rotation":[27,49,57],"invariant":[28,65],"deep":[29,66,82],"network":[31],"(CNN).":[32],"Results":[33,62],"are":[37],"combined":[38],"using":[39],"winner":[41],"takes":[42],"all":[43],"pooling":[44],"method":[45,112],"produce":[47],"approximate":[48],"invariance,":[50],"approximation":[53],"improving":[54],"smaller":[56],"increments":[58],"between":[59],"columns.":[61],"applying":[64],"CNN":[67,83],"MNIST":[70,92],"and":[71,94],"CHARS74K":[73,101],"rotated":[74],"test":[75],"data":[76],"showed":[77],"great":[78],"improvement":[79],"over":[80],"traditional":[81],"52.32%":[86],"increase":[87,98],"accuracy":[89,97],"on":[90,99],"dataset":[93],"36.44%":[96],"dataset.":[102],"also":[105],"introduces":[106],"Caffe":[108],"implementation":[109],"for":[113],"object":[116],"recognition":[117],"research.":[118]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
