{"id":"https://openalex.org/W3205591866","doi":"https://doi.org/10.3390/s21206763","title":"A Deep-Learning Based Visual Sensing Concept for a Robust Classification of Document Images under Real-World Hard Conditions","display_name":"A Deep-Learning Based Visual Sensing Concept for a Robust Classification of Document Images under Real-World Hard Conditions","publication_year":2021,"publication_date":"2021-10-12","ids":{"openalex":"https://openalex.org/W3205591866","doi":"https://doi.org/10.3390/s21206763","mag":"3205591866","pmid":"https://pubmed.ncbi.nlm.nih.gov/34695977"},"language":"en","primary_location":{"id":"doi:10.3390/s21206763","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21206763","pdf_url":"https://www.mdpi.com/1424-8220/21/20/6763/pdf?version=1634190133","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/21/20/6763/pdf?version=1634190133","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067686290","display_name":"Kabeh Mohsenzadegan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210166741","display_name":"University of Klagenfurt","ror":"https://ror.org/05q9m0937","country_code":"AT","type":"education","lineage":["https://openalex.org/I4210166741"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Kabeh Mohsenzadegan","raw_affiliation_strings":["Institute for Smart Systems Technologies, University Klagenfurt, 9020 Klagenfurt, Austria"],"affiliations":[{"raw_affiliation_string":"Institute for Smart Systems Technologies, University Klagenfurt, 9020 Klagenfurt, Austria","institution_ids":["https://openalex.org/I4210166741"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035234540","display_name":"Vahid Tavakkoli","orcid":null},"institutions":[{"id":"https://openalex.org/I4210166741","display_name":"University of Klagenfurt","ror":"https://ror.org/05q9m0937","country_code":"AT","type":"education","lineage":["https://openalex.org/I4210166741"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Vahid Tavakkoli","raw_affiliation_strings":["Institute for Smart Systems Technologies, University Klagenfurt, 9020 Klagenfurt, Austria"],"affiliations":[{"raw_affiliation_string":"Institute for Smart Systems Technologies, University Klagenfurt, 9020 Klagenfurt, Austria","institution_ids":["https://openalex.org/I4210166741"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061137052","display_name":"Kyandoghere Kyamakya","orcid":"https://orcid.org/0000-0003-0773-9476"},"institutions":[{"id":"https://openalex.org/I4210166741","display_name":"University of Klagenfurt","ror":"https://ror.org/05q9m0937","country_code":"AT","type":"education","lineage":["https://openalex.org/I4210166741"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Kyandoghere Kyamakya","raw_affiliation_strings":["Institute for Smart Systems Technologies, University Klagenfurt, 9020 Klagenfurt, Austria"],"affiliations":[{"raw_affiliation_string":"Institute for Smart Systems Technologies, University Klagenfurt, 9020 Klagenfurt, Austria","institution_ids":["https://openalex.org/I4210166741"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5067686290"],"corresponding_institution_ids":["https://openalex.org/I4210166741"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.7751,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.74125523,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"21","issue":"20","first_page":"6763","last_page":"6763"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9988999962806702,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9988999962806702,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9975000023841858,"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/T14319","display_name":"Currency Recognition and Detection","score":0.996399998664856,"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":0.7580952644348145},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7023496627807617},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6912975311279297},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.611869215965271},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6055616736412048},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6017409563064575},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47022581100463867},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4531528949737549},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.43268832564353943},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.41786524653434753},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41685691475868225},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.41190189123153687},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08631366491317749}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7580952644348145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7023496627807617},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6912975311279297},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.611869215965271},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6055616736412048},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6017409563064575},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47022581100463867},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4531528949737549},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.43268832564353943},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.41786524653434753},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41685691475868225},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.41190189123153687},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08631366491317749},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","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/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s21206763","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21206763","pdf_url":"https://www.mdpi.com/1424-8220/21/20/6763/pdf?version=1634190133","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:34695977","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34695977","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:9cbef28ddcf845e1ba12187fbb6d0db3","is_oa":true,"landing_page_url":"https://doaj.org/article/9cbef28ddcf845e1ba12187fbb6d0db3","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 21, Iss 20, p 6763 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/20/6763/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21206763","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 21; Issue 20; Pages: 6763","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8537789","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8537789","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s21206763","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21206763","pdf_url":"https://www.mdpi.com/1424-8220/21/20/6763/pdf?version=1634190133","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3205591866.pdf","grobid_xml":"https://content.openalex.org/works/W3205591866.grobid-xml"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W205301110","https://openalex.org/W1510710711","https://openalex.org/W1731296920","https://openalex.org/W1967838061","https://openalex.org/W2004665841","https://openalex.org/W2016053056","https://openalex.org/W2016626577","https://openalex.org/W2028571532","https://openalex.org/W2040511559","https://openalex.org/W2093612963","https://openalex.org/W2099937879","https://openalex.org/W2100495367","https://openalex.org/W2102605133","https://openalex.org/W2107699930","https://openalex.org/W2112796928","https://openalex.org/W2147800946","https://openalex.org/W2158262584","https://openalex.org/W2162741153","https://openalex.org/W2163605009","https://openalex.org/W2168809519","https://openalex.org/W2170204490","https://openalex.org/W2194775991","https://openalex.org/W2236864879","https://openalex.org/W2306317764","https://openalex.org/W2547018007","https://openalex.org/W2557738935","https://openalex.org/W2581082771","https://openalex.org/W2605976347","https://openalex.org/W2605982830","https://openalex.org/W2618530766","https://openalex.org/W2621023101","https://openalex.org/W2746982720","https://openalex.org/W2757561621","https://openalex.org/W2765739551","https://openalex.org/W2768160997","https://openalex.org/W2775758567","https://openalex.org/W2784313390","https://openalex.org/W2785529134","https://openalex.org/W2791460829","https://openalex.org/W2799289872","https://openalex.org/W2805671481","https://openalex.org/W2807436399","https://openalex.org/W2900859886","https://openalex.org/W2911303748","https://openalex.org/W2945981644","https://openalex.org/W2946753127","https://openalex.org/W2952454517","https://openalex.org/W2962772269","https://openalex.org/W2963420686","https://openalex.org/W2985321619","https://openalex.org/W2992075130","https://openalex.org/W2997604048","https://openalex.org/W2997924499","https://openalex.org/W3008806548","https://openalex.org/W3017424189","https://openalex.org/W3048422314","https://openalex.org/W3098297549","https://openalex.org/W3099895171","https://openalex.org/W3107425599","https://openalex.org/W6628691028","https://openalex.org/W6684191040","https://openalex.org/W6689700342","https://openalex.org/W6785007197"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2011676020","https://openalex.org/W2329895846"],"abstract_inverted_index":{"This":[0,95],"paper's":[1],"core":[2],"objective":[3],"is":[4,39,57,89,97,110,158],"to":[5,13,52],"develop":[6],"and":[7,29,67,100,107,148,161],"validate":[8],"a":[9,31,40,103,153,164],"new":[10],"neurocomputing":[11],"model":[12,109,157],"classify":[14],"document":[15,47,171],"images":[16,48],"in":[17,45,82,129],"particularly":[18],"demanding":[19],"hard":[20,123],"conditions":[21],"such":[22,142],"as":[23,143],"image":[24,26],"distortions,":[25],"size":[27],"variance":[28],"scale,":[30],"huge":[32],"number":[33],"of":[34,132,166],"classes,":[35],"etc.":[36],"Document":[37,55],"classification":[38,56,172],"special":[41],"machine":[42],"vision":[43],"task":[44,96],"which":[46],"are":[49],"categorized":[50],"according":[51],"their":[53,85],"likelihood.":[54],"by":[58,181,198],"itself":[59],"an":[60],"important":[61],"topic":[62],"for":[63,75,121],"the":[64,113,130,167,175,186,190],"digital":[65],"office":[66],"it":[68,192],"has":[69],"several":[70],"usages.":[71],"Additionally,":[72,174],"different":[73,183],"methods":[74],"solving":[76],"this":[77,151],"problem":[78],"have":[79],"been":[80],"presented":[81],"various":[83],"studies;":[84],"respectively":[86],"reached":[87],"performance":[88],"however":[90],"not":[91],"yet":[92],"good":[93],"enough.":[94],"very":[98],"tough":[99],"challenging.":[101],"Thus,":[102],"novel,":[104],"more":[105,204],"accurate":[106],"precise":[108],"needed.":[111],"Although":[112],"related":[114],"works":[115],"do":[116],"reach":[117],"acceptable":[118],"accuracy":[119],"values":[120],"less":[122],"conditions,":[124,137],"they":[125],"generally":[126],"fully":[127],"fail":[128],"face":[131],"those":[133],"above-mentioned":[134],"hard,":[135],"real-world":[136],"including,":[138],"amongst":[139],"others,":[140],"distortions":[141],"noise,":[144],"blur,":[145],"low":[146],"contrast,":[147],"shadows.":[149],"In":[150,189],"paper,":[152],"novel":[154],"deep":[155],"CNN":[156],"developed,":[159],"validated":[160],"benchmarked":[162],"with":[163],"selection":[165],"most":[168],"relevant":[169],"recent":[170],"models.":[173],"model's":[176],"sensitivity":[177],"was":[178],"significantly":[179],"improved":[180],"injecting":[182],"artifacts":[184],"during":[185],"training":[187],"process.":[188],"benchmarking,":[191],"does":[193],"clearly":[194],"outperform":[195],"all":[196],"others":[197],"at":[199],"least":[200],"4%,":[201],"thus":[202],"reaching":[203],"than":[205],"96%":[206],"accuracy.":[207]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}