{"id":"https://openalex.org/W2999165588","doi":"https://doi.org/10.1109/wacv45572.2020.9093396","title":"A Novel Inspection System For Variable Data Printing Using Deep Learning","display_name":"A Novel Inspection System For Variable Data Printing Using Deep Learning","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W2999165588","doi":"https://doi.org/10.1109/wacv45572.2020.9093396","mag":"2999165588"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2001.04325","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053547928","display_name":"Oren Haik","orcid":"https://orcid.org/0000-0003-4344-507X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oren Haik","raw_affiliation_strings":["HP Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HP Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013530117","display_name":"Oded Perry","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oded Perry","raw_affiliation_strings":["HP Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HP Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012983652","display_name":"Eli Chen","orcid":"https://orcid.org/0000-0002-8105-6537"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eli Chen","raw_affiliation_strings":["HP Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HP Inc","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010390231","display_name":"Peter Klammer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peter Klammer","raw_affiliation_strings":["HP Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HP Inc","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01543633,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3530","last_page":"3539"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9984999895095825,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9923999905586243,"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":0.8035821914672852},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7394027709960938},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.6352030038833618},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6257849931716919},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.5398174524307251},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.503250777721405},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.49510493874549866},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.494295597076416},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4856635332107544},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48195216059684753},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.476020872592926},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4644942581653595},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.43933480978012085},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4370788335800171},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3693242073059082},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07699522376060486},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0699370801448822}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8035821914672852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7394027709960938},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6352030038833618},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6257849931716919},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.5398174524307251},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.503250777721405},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.49510493874549866},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.494295597076416},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4856635332107544},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48195216059684753},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.476020872592926},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4644942581653595},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.43933480978012085},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4370788335800171},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3693242073059082},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07699522376060486},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0699370801448822},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2001.04325","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.04325","pdf_url":"https://arxiv.org/pdf/2001.04325","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2999165588","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2001.04325v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2001.04325","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2001.04325","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2001.04325","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.04325","pdf_url":"https://arxiv.org/pdf/2001.04325","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2999165588.pdf","grobid_xml":"https://content.openalex.org/works/W2999165588.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1955055330","https://openalex.org/W1990236366","https://openalex.org/W2004313226","https://openalex.org/W2013181094","https://openalex.org/W2058835961","https://openalex.org/W2133665775","https://openalex.org/W2169966850","https://openalex.org/W2170140722","https://openalex.org/W2183136502","https://openalex.org/W2560474170","https://openalex.org/W2563786098","https://openalex.org/W2613718673","https://openalex.org/W2746440905","https://openalex.org/W2757948293","https://openalex.org/W2764034829","https://openalex.org/W2770376515","https://openalex.org/W2772778553","https://openalex.org/W2781926312","https://openalex.org/W2782522152","https://openalex.org/W2782995645","https://openalex.org/W2787091153","https://openalex.org/W2788945392","https://openalex.org/W2799261915","https://openalex.org/W2805152403","https://openalex.org/W2890747436","https://openalex.org/W2891248708","https://openalex.org/W2891336752","https://openalex.org/W2894403074","https://openalex.org/W2894844962","https://openalex.org/W2895975145","https://openalex.org/W2901077311","https://openalex.org/W2914666560","https://openalex.org/W2932306369","https://openalex.org/W2962842723","https://openalex.org/W2962922299","https://openalex.org/W2963150697","https://openalex.org/W2963524571","https://openalex.org/W2963653539","https://openalex.org/W2963698633","https://openalex.org/W2963782415","https://openalex.org/W2964052394","https://openalex.org/W2964087130","https://openalex.org/W2986812626","https://openalex.org/W2990943125","https://openalex.org/W3010257550","https://openalex.org/W3106250896","https://openalex.org/W3198390318","https://openalex.org/W6620707391","https://openalex.org/W6639824700","https://openalex.org/W6755020528","https://openalex.org/W6755049344","https://openalex.org/W6755268938","https://openalex.org/W6756308226","https://openalex.org/W6760219190","https://openalex.org/W6769694436","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W3024176522","https://openalex.org/W3161819727","https://openalex.org/W3004489678","https://openalex.org/W3159774911","https://openalex.org/W3156616918","https://openalex.org/W3141138843","https://openalex.org/W3044622341","https://openalex.org/W3099576037","https://openalex.org/W3089323275","https://openalex.org/W3174526971","https://openalex.org/W2914993068","https://openalex.org/W2974818407","https://openalex.org/W3033471827","https://openalex.org/W2944930110","https://openalex.org/W3121968065","https://openalex.org/W3127917938","https://openalex.org/W3210218269","https://openalex.org/W3185414317","https://openalex.org/W1554006700","https://openalex.org/W3011043518"],"abstract_inverted_index":{"We":[0,123],"present":[1],"a":[2,30,35,99,134,147],"novel":[3],"approach":[4,132],"for":[5,75],"inspecting":[6],"variable":[7],"data":[8],"prints":[9],"(VDP)":[10],"with":[11,133],"an":[12,39,88],"ultra-low":[13],"false":[14],"alarm":[15],"rate":[16],"(0.005%)":[17],"and":[18,38,83],"potential":[19],"applicability":[20],"to":[21],"other":[22],"real-world":[23,138],"problems.":[24],"The":[25,45,85,103],"system":[26],"is":[27,48,87],"based":[28],"on":[29,146,164],"comparison":[31,46],"between":[32],"two":[33,71,95],"images:":[34],"reference":[36],"image":[37,40],"captured":[41],"by":[42,114],"low-cost":[43,51],"scanners.":[44],"task":[47],"challenging":[49],"as":[50,61],"imaging":[52],"systems":[53],"create":[54],"artifacts":[55],"that":[56,92],"may":[57],"erroneously":[58],"be":[59],"classified":[60],"true":[62],"(genuine)":[63],"defects.":[64],"To":[65],"address":[66],"this":[67,165],"challenge":[68],"we":[69,142],"introduce":[70],"new":[72],"fusion":[73,90],"methods,":[74],"change":[76,153],"detection":[77,154],"applications,":[78],"which":[79],"are":[80],"both":[81],"fast":[82],"efficient.":[84],"first":[86],"early":[89],"method":[91,158],"combines":[93],"the":[94,112,118,121,125,128,161],"input":[96],"images":[97],"into":[98],"single":[100],"pseudo-color":[101],"image.":[102],"second,":[104],"called":[105],"Change-Detection":[106],"Single":[107],"Shot":[108],"Detector":[109],"(CD-SSD)":[110],"leverages":[111],"SSD":[113],"fusing":[115],"features":[116],"in":[117],"middle":[119],"of":[120,127,150],"network.":[122],"demonstrate":[124],"effectiveness":[126],"proposed":[129],"deep":[130],"learning-based":[131],"large":[135],"dataset":[136],"from":[137],"printing":[139],"scenarios.":[140],"Finally,":[141],"evaluate":[143],"our":[144],"models":[145],"different":[148],"domain":[149],"aerial":[151],"imagery":[152],"(AICD).":[155],"Our":[156],"best":[157],"clearly":[159],"outperforms":[160],"state-of-the-art":[162],"baseline":[163],"dataset.":[166]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
