{"id":"https://openalex.org/W4416136017","doi":"https://doi.org/10.48550/arxiv.2506.05026","title":"Physical Annotation for Automated Optical Inspection: A Concept for In-Situ, Pointer-Based Training Data Generation","display_name":"Physical Annotation for Automated Optical Inspection: A Concept for In-Situ, Pointer-Based Training Data Generation","publication_year":2025,"publication_date":"2025-06-05","ids":{"openalex":"https://openalex.org/W4416136017","doi":"https://doi.org/10.48550/arxiv.2506.05026"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2506.05026","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.05026","pdf_url":"https://arxiv.org/pdf/2506.05026","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.05026","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093809520","display_name":"Oliver Krumpek","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Krumpek, Oliver","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024983886","display_name":"Oliver Heimann","orcid":"https://orcid.org/0000-0001-7310-7528"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heimann, Oliver","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065074078","display_name":"J\u00f6rg Kr\u00fcger","orcid":"https://orcid.org/0000-0001-5138-0793"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kr\u00fcger, J\u00f6rg","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.3375999927520752,"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":0.3375999927520752,"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/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.04569999873638153,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.03779999911785126,"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/annotation","display_name":"Annotation","score":0.8723000288009644},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.7113999724388123},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6581000089645386},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.6035000085830688},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4456000030040741},{"id":"https://openalex.org/keywords/automatic-image-annotation","display_name":"Automatic image annotation","score":0.4092000126838684},{"id":"https://openalex.org/keywords/user-interface","display_name":"User interface","score":0.3824000060558319},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.32839998602867126}],"concepts":[{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.8723000288009644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7688000202178955},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7113999724388123},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6581000089645386},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.6035000085830688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46950000524520874},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4456000030040741},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.4092000126838684},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.3824000060558319},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.36059999465942383},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3172000050544739},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.313400000333786},{"id":"https://openalex.org/C37789001","wikidata":"https://www.wikidata.org/wiki/Q782543","display_name":"Graphical user interface","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2980000078678131},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.28630000352859497},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27399998903274536},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.26170000433921814}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2506.05026","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.05026","pdf_url":"https://arxiv.org/pdf/2506.05026","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.05026","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.05026","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.05026","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.05026","pdf_url":"https://arxiv.org/pdf/2506.05026","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416136017.pdf","grobid_xml":"https://content.openalex.org/works/W4416136017.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,172],"paper":[1,173],"introduces":[2],"a":[3,34,57,95],"novel":[4],"physical":[5,48],"annotation":[6,43,85,92,110,157],"system":[7,18,46,176],"designed":[8],"to":[9,23,63,73,105,133,135,188],"generate":[10],"training":[11,38,138,146],"data":[12,128,191],"for":[13,168,193],"automated":[14,127,194],"optical":[15,195],"inspection.":[16,196],"The":[17,66,117],"uses":[19,69],"pointer-based":[20],"in-situ":[21],"interaction":[22],"transfer":[24],"the":[25,54,103,109,121,136,142,152,166,175],"valuable":[26,145],"expertise":[27,125],"of":[28,144,154],"trained":[29],"inspection":[30],"personnel":[31],"directly":[32,52],"into":[33,83],"machine":[35],"learning":[36],"(ML)":[37],"pipeline.":[39],"Unlike":[40],"conventional":[41],"screen-based":[42],"methods,":[44],"our":[45],"captures":[47],"trajectories":[49,158],"and":[50,60,78,115,126,140,159,180,183],"contours":[51],"on":[53],"object,":[55],"providing":[56],"more":[58],"intuitive":[59],"efficient":[61],"way":[62],"label":[64],"data.":[65],"core":[67],"technology":[68],"calibrated,":[70],"tracked":[71],"pointers":[72],"accurately":[74],"record":[75],"user":[76],"input":[77],"transform":[79],"these":[80],"spatial":[81],"interactions":[82],"standardised":[84],"formats":[86],"that":[87,161],"are":[88],"compatible":[89],"with":[90,163],"open-source":[91],"software.":[93],"Additionally,":[94],"simple":[96],"projector-based":[97],"interface":[98,181],"projects":[99],"visual":[100],"guidance":[101],"onto":[102],"object":[104],"assist":[106],"users":[107],"during":[108],"process,":[111],"ensuring":[112],"greater":[113],"accuracy":[114],"consistency.":[116],"proposed":[118],"concept":[119],"bridges":[120],"gap":[122],"between":[123],"human":[124],"generation,":[129],"enabling":[130],"non-IT":[131],"experts":[132],"contribute":[134],"ML":[137,170,190],"pipeline":[139],"preventing":[141],"loss":[143],"samples.":[147],"Preliminary":[148],"evaluation":[149],"results":[150],"confirm":[151],"feasibility":[153],"capturing":[155],"detailed":[156],"demonstrate":[160],"integration":[162],"CVAT":[164],"streamlines":[165],"workflow":[167],"subsequent":[169],"tasks.":[171],"details":[174],"architecture,":[177],"calibration":[178],"procedures":[179],"design,":[182],"discusses":[184],"its":[185],"potential":[186],"contribution":[187],"future":[189],"generation":[192]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}