{"id":"https://openalex.org/W2017396861","doi":"https://doi.org/10.5220/0005125700370044","title":"Localization of Visual Codes in the DCT Domain Using Deep Rectifier Neural Networks","display_name":"Localization of Visual Codes in the DCT Domain Using Deep Rectifier Neural Networks","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2017396861","doi":"https://doi.org/10.5220/0005125700370044","mag":"2017396861"},"language":"en","primary_location":{"id":"doi:10.5220/0005125700370044","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0005125700370044","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0005125700370044","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044330162","display_name":"P\u00e9ter Bodn\u00e1r","orcid":"https://orcid.org/0000-0002-5302-612X"},"institutions":[{"id":"https://openalex.org/I227486990","display_name":"University of Szeged","ror":"https://ror.org/01pnej532","country_code":"HU","type":"education","lineage":["https://openalex.org/I227486990"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"P\u00e9ter Bodn\u00e1r","raw_affiliation_strings":["University of Szeged, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Szeged, Hungary","institution_ids":["https://openalex.org/I227486990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058277119","display_name":"Tam\u00e1s Gr\u00f3sz","orcid":"https://orcid.org/0000-0001-7918-9579"},"institutions":[{"id":"https://openalex.org/I227486990","display_name":"University of Szeged","ror":"https://ror.org/01pnej532","country_code":"HU","type":"education","lineage":["https://openalex.org/I227486990"]},{"id":"https://openalex.org/I7597260","display_name":"Hungarian Academy of Sciences","ror":"https://ror.org/02ks8qq67","country_code":"HU","type":"government","lineage":["https://openalex.org/I7597260"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Tam\u00e1s Gr\u00f3sz","raw_affiliation_strings":["Hungarian Academy of Sciences and University of Szeged, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hungarian Academy of Sciences and University of Szeged, Hungary","institution_ids":["https://openalex.org/I227486990","https://openalex.org/I7597260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020608163","display_name":"L\u00e1szl\u00f3 T\u00f3th","orcid":"https://orcid.org/0000-0003-0161-1375"},"institutions":[{"id":"https://openalex.org/I227486990","display_name":"University of Szeged","ror":"https://ror.org/01pnej532","country_code":"HU","type":"education","lineage":["https://openalex.org/I227486990"]},{"id":"https://openalex.org/I7597260","display_name":"Hungarian Academy of Sciences","ror":"https://ror.org/02ks8qq67","country_code":"HU","type":"government","lineage":["https://openalex.org/I7597260"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"L\u00e1szl\u00f3 T\u00f3th","raw_affiliation_strings":["Hungarian Academy of Sciences and University of Szeged, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hungarian Academy of Sciences and University of Szeged, Hungary","institution_ids":["https://openalex.org/I227486990","https://openalex.org/I7597260"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043504365","display_name":"L\u00e1szl\u00f3 G. Ny\u00fal","orcid":"https://orcid.org/0000-0002-3826-543X"},"institutions":[{"id":"https://openalex.org/I227486990","display_name":"University of Szeged","ror":"https://ror.org/01pnej532","country_code":"HU","type":"education","lineage":["https://openalex.org/I227486990"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"L\u00e1szl\u00f3 G. Ny\u00fal","raw_affiliation_strings":["University of Szeged, Hungary","Szegedi Tudomanyegyetem"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Szeged, Hungary","institution_ids":["https://openalex.org/I227486990"]},{"raw_affiliation_string":"Szegedi Tudomanyegyetem","institution_ids":["https://openalex.org/I227486990"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5137,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55918828,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"37","last_page":"44"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9923999905586243,"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"}},"topics":[{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9923999905586243,"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":0.6902559399604797},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.603630006313324},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.5724863409996033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5333830118179321},{"id":"https://openalex.org/keywords/rectifier","display_name":"Rectifier (neural networks)","score":0.514295756816864},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5131672024726868},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.49927306175231934},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.396530419588089},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34829872846603394},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.179835706949234},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1613585650920868},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15838438272476196},{"id":"https://openalex.org/keywords/types-of-artificial-neural-networks","display_name":"Types of artificial neural networks","score":0.13940471410751343}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6902559399604797},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.603630006313324},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.5724863409996033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5333830118179321},{"id":"https://openalex.org/C50100734","wikidata":"https://www.wikidata.org/wiki/Q7303176","display_name":"Rectifier (neural networks)","level":5,"score":0.514295756816864},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5131672024726868},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.49927306175231934},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.396530419588089},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34829872846603394},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.179835706949234},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1613585650920868},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15838438272476196},{"id":"https://openalex.org/C177973122","wikidata":"https://www.wikidata.org/wiki/Q7860946","display_name":"Types of artificial neural networks","level":4,"score":0.13940471410751343},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5220/0005125700370044","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0005125700370044","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:publicatio.bibl.u-szeged.hu:4640","is_oa":true,"landing_page_url":"http://publicatio.bibl.u-szeged.hu/4640/1/ANNIIP2014.pdf","pdf_url":"http://publicatio.bibl.u-szeged.hu/4640/1/ANNIIP2014.pdf","source":{"id":"https://openalex.org/S4306400675","display_name":"SZTE Publicatio Repozit\u00f3rium (University of Szeged)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I227486990","host_organization_name":"University of Szeged","host_organization_lineage":["https://openalex.org/I227486990"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"K\u00f6nyv r\u00e9sze"}],"best_oa_location":{"id":"doi:10.5220/0005125700370044","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0005125700370044","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W2013615594","https://openalex.org/W2048438392","https://openalex.org/W2101880676","https://openalex.org/W2136922672","https://openalex.org/W2139923216","https://openalex.org/W2160306971","https://openalex.org/W2275765369","https://openalex.org/W2539990263"],"related_works":["https://openalex.org/W2055682261","https://openalex.org/W1916685473","https://openalex.org/W1993363272","https://openalex.org/W2174937762","https://openalex.org/W2186390138","https://openalex.org/W2790129917","https://openalex.org/W2060035984","https://openalex.org/W2992856432","https://openalex.org/W2054459866","https://openalex.org/W2212883587"],"abstract_inverted_index":{"The":[0],"reading":[1],"process":[2],"of":[3,7,67],"visual":[4],"codes":[5,102],"consists":[6],"two":[8],"steps,":[9],"localization":[10,22],"and":[11,48,72,80,85],"data":[12,74],"decoding.This":[13],"paper":[14],"presents":[15],"a":[16],"novel":[17],"method":[18],"for":[19,92],"QR":[20,93],"code":[21,106],"using":[23],"deep":[24],"rectifier":[25],"neural":[26,69],"networks,":[27,70],"trained":[28],"directly":[29],"in":[30,63],"the":[31,68],"JPEG":[32,58],"DCT":[33],"domain,":[34],"thus":[35],"making":[36],"image":[37],"decompression":[38],"unnecessary.This":[39],"approach":[40,88],"is":[41,89],"efficient":[42],"with":[43],"respect":[44],"to":[45,99],"both":[46],"storage":[47],"computation":[49],"cost,":[50],"being":[51],"convenient,":[52],"since":[53],"camera":[54],"hardware":[55],"can":[56,96],"provide":[57],"stream":[59],"as":[60,108],"their":[61],"output":[62],"many":[64],"cases.The":[65],"structure":[66],"regularization,":[71],"training":[73],"parameters,":[75],"like":[76],"input":[77],"vector":[78],"length":[79],"compression":[81],"level,":[82],"are":[83],"evaluated":[84],"discussed.The":[86],"proposed":[87],"not":[90],"exclusively":[91],"codes,":[94],"but":[95],"be":[97],"adapted":[98],"Data":[100],"Matrix":[101],"or":[103],"other":[104],"two-dimensional":[105],"types":[107],"well.":[109]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}