{"id":"https://openalex.org/W6894148440","doi":"https://doi.org/10.5445/ir/1000173990","title":"Towards Learning Object Detectors with Limited Data for Industrial Applications","display_name":"Towards Learning Object Detectors with Limited Data for Industrial Applications","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W6894148440","doi":"https://doi.org/10.5445/ir/1000173990"},"language":"de","primary_location":{"id":"pmh:oai:EVASTAR-Karlsruhe.de:1000173990","is_oa":false,"landing_page_url":"https://publikationen.bibliothek.kit.edu/1000173990","pdf_url":null,"source":{"id":"https://openalex.org/S4306401992","display_name":"Repository KITopen (Karlsruhe Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102335020","host_organization_name":"Karlsruhe Institute of Technology","host_organization_lineage":["https://openalex.org/I102335020"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/doctoralThesis"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://library.oapen.org/handle/20.500.12657/100728","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Guirguis, Karim","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Guirguis, Karim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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":true,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.49459999799728394,"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":0.49459999799728394,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.06499999761581421,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.03550000116229057,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/object","display_name":"Object (grammar)","score":0.32820001244544983},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.19760000705718994},{"id":"https://openalex.org/keywords/research-object","display_name":"Research Object","score":0.15780000388622284}],"concepts":[{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3269999921321869},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.3005000054836273},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.24279999732971191},{"id":"https://openalex.org/C15708023","wikidata":"https://www.wikidata.org/wiki/Q80083","display_name":"Humanities","level":1,"score":0.23749999701976776},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.2168000042438507},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.19939999282360077},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.19760000705718994},{"id":"https://openalex.org/C153911025","wikidata":"https://www.wikidata.org/wiki/Q7202","display_name":"Molecular biology","level":1,"score":0.15870000422000885},{"id":"https://openalex.org/C2778631480","wikidata":"https://www.wikidata.org/wiki/Q17143022","display_name":"Research Object","level":2,"score":0.15780000388622284}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:EVASTAR-Karlsruhe.de:1000173990","is_oa":false,"landing_page_url":"https://publikationen.bibliothek.kit.edu/1000173990","pdf_url":null,"source":{"id":"https://openalex.org/S4306401992","display_name":"Repository KITopen (Karlsruhe Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102335020","host_organization_name":"Karlsruhe Institute of Technology","host_organization_lineage":["https://openalex.org/I102335020"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/doctoralThesis"},{"id":"pmh:oai:directory.doabooks.org:20.500.12854/158411","is_oa":true,"landing_page_url":"https://library.oapen.org/handle/20.500.12657/100728","pdf_url":null,"source":{"id":"https://openalex.org/S4306400539","display_name":"Directory of Open access Books (OAPEN Foundation)","issn_l":null,"issn":null,"is_oa":false,"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":null},{"id":"doi:10.5445/ir/1000173990","is_oa":true,"landing_page_url":"https://doi.org/10.5445/ir/1000173990","pdf_url":null,"source":{"id":"https://openalex.org/S7407052948","display_name":"KITopen","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Book"}],"best_oa_location":{"id":"pmh:oai:directory.doabooks.org:20.500.12854/158411","is_oa":true,"landing_page_url":"https://library.oapen.org/handle/20.500.12657/100728","pdf_url":null,"source":{"id":"https://openalex.org/S4306400539","display_name":"Directory of Open access Books (OAPEN Foundation)","issn_l":null,"issn":null,"is_oa":false,"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":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.40415388345718384,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"K\u00fcnstliche":[0],"Intelligenz":[1],"(KI)":[2],"hat":[3,19],"die":[4,95,116,162,204,250,299,302,305,374,392,398,449,509],"Produktionstechnik":[5],"in":[6,71,83,106,211,254,272,288,304,468,477,533,540,544],"der":[7,24,230,289,320,390,454],"Industrie":[8],"bereits":[9,103,200],"revolutioniert":[10],"und":[11,34,61,79,112,123,126,133,229,235,309,347,357,386,397,423,445,500,513,516,536,547],"wird":[12,21,263,287,365,382],"diese":[13,146,163,278,314,435,528],"zuk\u00fcnftig":[14],"weitgehend":[15],"ver\u00e4ndern.":[16],"Diese":[17,64],"Transformation":[18],"bzw.":[20,166,275],"abh\u00e4ngig":[22],"von":[23,29,36,43,97,131,148,172,269,342],"jeweiligen":[25],"Branche":[26],"zu":[27,31,38,55,59,74,77,88,110,113,151,206,214,223,316,360,429,480],"Kostensenkungen":[28],"bis":[30,37],"ca.":[32,39],"$20\\%$":[33],"Umsatzsteigerungen":[35],"$10\\%$":[40],"f\u00fchren.":[41,217],"Mithilfe":[42],"KI":[44],"ist":[45],"es":[46,67],"IT-Systemen":[47],"nun":[48],"m\u00f6glich,":[49],"gro\u00dfe":[50],"Datenmengen":[51],"aus":[52,319,489],"Produktionslinien":[53],"effizient":[54],"verarbeiten,":[56],"Schlussfolgerungen":[57],"daraus":[58],"ziehen":[60],"Optimierungen":[62],"durchzuf\u00fchren.":[63],"F\u00e4higkeiten":[65],"erm\u00f6glichen":[66],"diesen":[68,478,525],"Systemen,":[69],"Muster":[70],"den":[72,259,296,317,430,534],"Daten":[73,143,173,276],"erkennen,":[75],"Prozessverhalten":[76],"analysieren":[78],"vorherzusagen":[80],"sowie":[81],"Anomalien":[82],"Echtzeit":[84],"w\u00e4hrend":[85,280],"des":[86,157,281],"Produktionsprozesses":[87],"erkennen.":[89,114],"Eine":[90,494],"wichtige":[91],"Rolle":[92],"nimmt":[93],"hierbei":[94],"Perzeption":[96],"Objekten":[98],"ein,":[99,344],"um":[100,351,474],"beispielweise":[101],"zuvor":[102,134,199],"bekannte":[104],"Objekte":[105,125,165],"unterschiedlichen":[107,212,521],"Umgebungen":[108],"pr\u00e4zise":[109],"lokalisieren":[111],"F\u00fcr":[115],"Skalierung":[117],"solcher":[118],"Perzeptionsmodelle":[119],"auf":[120,155,409,461],"neue":[121,246,293,358,376],"Produkte":[122],"unbekannte":[124],"dem":[127,273,410],"damit":[128,369],"verbundenem":[129],"Training":[130],"neuen":[132,164],"nicht":[135],"bekannten":[136],"Klassen":[137,167,279,359,377],"werden":[138,244,379,465,508],"normalerweise":[139],"sehr":[140],"viele":[141],"annotierte":[142],"ben\u00f6tigt.":[144],"Um":[145],"Menge":[147],"ben\u00f6tigten":[149],"Trainingsdaten":[150],"reduzieren,":[152],"k\u00f6nnen":[153,537],"Modelle":[154],"Basis":[156],"Few-Shot-Object-Detection":[158],"(FSOD)-Ansatzes":[159],"eingesetzt":[160,464,551],"werden,":[161],"anhand":[168],"einer":[169],"begrenzten":[170],"Anzahl":[171],"erlernen":[174],"k\u00f6nnen.":[175,380],"Allerdings":[176],"haben":[177],"aktuelle":[178],"FSOD-Algorithmen":[179],"zwei":[180],"Hauptnachteile.":[181],"Sie":[182],"sind":[183,219],"erstens":[184],"anf\u00e4llig":[185],"f\u00fcr":[186,295,355],"das":[187,251,267,345,488],"sogenannte":[188],"\u201ekatastrophale":[189],"Vergessen\u201c":[190],"beim":[191],"Erlernen":[192],"neuer":[193],"Klassen,":[194],"da":[195],"sie":[196,220],"dazu":[197],"tendieren,":[198],"erlerntes":[201],"Wissen":[202,268],"\u00fcber":[203,266,277,373],"Basis-Klassen":[205,270],"vergessen.":[207],"Dieses":[208],"Ph\u00e4nomen":[209],"kann":[210],"Situationen":[213],"verschiedenen":[215],"Fehlern":[216],"Zweitens":[218],"im":[221,331,400,427,438,548],"Vergleich":[222,428],"anderen":[224,311],"Ans\u00e4tzen":[225],"aufgrund":[226,419],"ihrer":[227],"Komplexit\u00e4t":[228],"hohen":[231],"Modellkapazit\u00e4t":[232],"viel":[233],"rechenaufw\u00e4ndiger":[234],"weisen":[236],"eine":[237,292,352,366,496,498,501],"verminderte":[238],"Genauigkeit":[239],"auf.":[240],"In":[241,258,524],"dieser":[242,469,506],"Dissertation":[243],"drei":[245,405,436,529],"\u201eGeneralized-Few-Shot-Object-Detection\u201c":[247],"(G-FSOD)-Ans\u00e4tze":[248],"vorgestellt,":[249],"katastrophale":[252],"Vergessen":[253,265],"neuronalen":[255],"Netzen":[256],"untersuchen.":[257],"ersten":[260,290],"beiden":[261],"Verfahren":[262,335,395,407,511,530],"dieses":[264,394],"verringert,":[271],"Informationen":[274,372],"Trainings":[282],"noch":[283],"vorhanden":[284],"sind.":[285,324],"Hierf\u00fcr":[286],"Methode":[291],"Gradienten-Update-Regel":[294],"Trainingsprozess":[297],"vorgeschlagen,":[298],"zum":[300,310],"einen":[301,328,384],"Gradienten":[303,315,318],"richtige":[306],"Richtung":[307],"lenkt":[308],"sicherstellt,":[312],"dass":[313],"Basis-Klasse":[321],"\u00e4hnlich":[322],"ausgerichtet":[323],"Dies":[325,381],"erm\u00f6glicht":[326],"gleichzeitig":[327],"effektiven":[329],"Informationsaustausch":[330],"Training.":[332],"Das":[333,415],"zweite":[334],"f\u00fchrt":[336],"ein":[337,484],"progressives":[338],"Netzwerk":[339],"zur":[340,440,452],"Verfeinerung":[341],"Objektvorschl\u00e4gen":[343],"aleatorische":[346],"epistemische":[348],"Unsicherheiten":[349],"nutzt,":[350],"robustere":[353],"Repr\u00e4sentation":[354],"alte":[356],"erlernen.":[361],"Im":[362],"dritten":[363],"Ansatz":[364],"\u201eKnowledge-Distillation\u201c":[367],"eingef\u00fchrt,":[368],"auch":[370,460,539],"ohne":[371],"Basis-Daten":[375,399],"gelernt":[378],"durch":[383],"eigenst\u00e4ndigen":[385],"leichtgewichtigen":[387],"Feature-Generator":[388],"sichergestellt,":[389],"zugleich":[391],"Hauptidee":[393],"widerspiegelt":[396],"hochdimensionalem":[401],"Feature-Raum":[402],"repliziert.":[403],"Alle":[404],"entwickelten":[406],"basieren":[408],"Decoupled":[411],"Faster":[412],"R-CNN":[413],"(DeFRCN)-Modell.":[414],"DeFRCN":[416],"wurde":[417,483],"verwendet":[418],"seiner":[420,424],"hervorragenden":[421],"Leistungsf\u00e4higkeit":[422],"einfacheren":[425],"Architektur":[426],"Transformer-basierten":[431],"Modellen.":[432],"Au\u00dferdem":[433],"stehen":[434],"Ans\u00e4tze":[437],"Gegensatz":[439],"h\u00e4ufig":[441],"verwendeten,":[442],"jedoch":[443],"teureren":[444],"weniger":[446],"effizienten":[447],"\u201eModellinversionstechnik\u201c,":[448],"iterative":[450],"Optimierungsverfahren":[451],"Rekonstruktion":[453],"Eingangsdaten":[455],"nutzt.":[456],"Damit":[457],"solche":[458],"FSOD-Modelle":[459],"eingebetteten":[462],"Rechenplattformen":[463],"k\u00f6nnen,":[466],"wurden":[467],"Arbeit":[470,507],"zus\u00e4tzlich":[471],"Methoden":[472],"untersucht,":[473],"vorhandene":[475],"Bottlenecks":[476],"FSOD-Architekturen":[479],"reduzieren.":[481],"Dazu":[482],"ressourceneffizienteres":[485],"FSOD-Modell":[486],"entwickelt,":[487],"folgenden":[490],"vier":[491],"Hauptkomponenten":[492],"besteht:":[493],"Multiskalen-Feature-Fusion,":[495],"Multi-Way-Support-Trainingstrategie,":[497],"Multiskalen-Datenaugmentation":[499],"adaptive":[502],"Klassen-Prototyping-Technik.":[503],"Am":[504],"Schluss":[505],"vorgestellten":[510],"validiert":[512],"umfangreiche":[514],"qualitative":[515],"quantitative":[517],"Experimente":[518],"an":[519],"mehreren":[520],"Datens\u00e4tzen":[522],"durchgef\u00fchrt.":[523],"Experimenten":[526],"erzielen":[527],"state-of-the-art":[531],"Ergebnisse":[532],"FSOD-Benchmarks":[535],"somit":[538],"vielen":[541],"praktischen":[542],"Anwendungen":[543],"realen":[545],"Szenarien":[546],"industriellen":[549],"Umfeld":[550],"werden.":[552]},"counts_by_year":[],"updated_date":"2026-08-09T07:27:16.801131","created_date":"2025-10-10T00:00:00"}
