{"id":"https://openalex.org/W4416959587","doi":"https://doi.org/10.48550/arxiv.2512.01315","title":"FOD-S2R: A FOD Dataset for Sim2Real Transfer Learning based Object Detection","display_name":"FOD-S2R: A FOD Dataset for Sim2Real Transfer Learning based Object Detection","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W4416959587","doi":"https://doi.org/10.48550/arxiv.2512.01315"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.01315","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.01315","pdf_url":"https://arxiv.org/pdf/2512.01315","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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","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/2512.01315","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016177841","display_name":"A. Vashist","orcid":"https://orcid.org/0000-0002-6318-7226"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Vashist, Ashish","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106356742","display_name":"Qiranul Saadiyean","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saadiyean, Qiranul","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100765440","display_name":"Suresh Sundaram","orcid":"https://orcid.org/0000-0001-6275-0921"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sundaram, Suresh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5005652970","display_name":"Chandra Sekhar Seelamantula","orcid":"https://orcid.org/0000-0001-9049-1912"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seelamantula, Chandra Sekhar","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016177841"],"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/T10036","display_name":"Advanced Neural Network Applications","score":0.8181999921798706,"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":0.8181999921798706,"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":0.02889999933540821,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.027300000190734863,"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-detection","display_name":"Object detection","score":0.7386999726295471},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.614300012588501},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.5450999736785889},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5432999730110168},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5263000130653381},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5149999856948853},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4749000072479248},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4309000074863434}],"concepts":[{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7386999726295471},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6269000172615051},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.614300012588501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6129000186920166},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.5450999736785889},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5432999730110168},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5263000130653381},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5149999856948853},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4749000072479248},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4309000074863434},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.40220001339912415},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3984000086784363},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3910999894142151},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3427000045776367},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3156000077724457},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2705000042915344},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26159998774528503},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.25589999556541443},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C2908613842","wikidata":"https://www.wikidata.org/wiki/Q108284447","display_name":"Aviation accident","level":3,"score":0.250900000333786},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.25060001015663147},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2512.01315","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.01315","pdf_url":"https://arxiv.org/pdf/2512.01315","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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.01315","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.01315","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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2512.01315","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.01315","pdf_url":"https://arxiv.org/pdf/2512.01315","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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","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":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4416959587.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Foreign":[0],"Object":[1],"Debris":[2],"(FOD)":[3],"within":[4,63],"aircraft":[5,66],"fuel":[6,13,42,67,116],"tanks":[7],"presents":[8],"critical":[9],"safety":[10],"hazards":[11],"including":[12],"contamination,":[14],"system":[15],"malfunctions,":[16],"and":[17,57,145,162,177,187,205],"increased":[18],"maintenance":[19],"costs.":[20],"Despite":[21],"the":[22,36,61,82,87,94,120,164,184,195,202,207],"severity":[23],"of":[24,32,55,60,89,107,134,137,166,197],"these":[25],"risks,":[26],"there":[27],"is":[28,81,132],"a":[29,50,64,114,211],"notable":[30],"lack":[31],"dedicated":[33],"datasets":[34,71],"for":[35,214,220],"complex,":[37],"enclosed":[38],"environments":[39],"found":[40],"inside":[41],"tanks.":[43],"To":[44],"bridge":[45],"this":[46],"gap,":[47,209],"we":[48,170],"present":[49],"novel":[51],"dataset,":[52],"FOD-S2R,":[53],"composed":[54,133],"real":[56],"synthetic":[58,90,121,153,181,198],"images":[59,111,125],"FOD":[62,96,217],"simulated":[65],"tank.":[68],"Unlike":[69],"existing":[70],"that":[72,152,179],"focus":[73],"on":[74,158],"external":[75],"or":[76],"open-air":[77],"environments,":[78],"our":[79],"dataset":[80,131],"first":[83],"to":[84,189],"systematically":[85],"evaluate":[86],"effectiveness":[88,196],"data":[91,154,182,199],"in":[92,99,113,200],"enhancing":[93,201],"real-world":[95,104,160,190],"detection":[97,175,185,218],"performance":[98,204],"confined,":[100],"closed":[101],"structures.":[102],"The":[103,130],"subset":[105,122],"consists":[106],"3,114":[108],"high-resolution":[109],"HD":[110],"captured":[112],"controlled":[115],"tank":[117],"replica,":[118],"while":[119],"includes":[123],"3,137":[124],"generated":[126],"using":[127],"Unreal":[128],"Engine.":[129],"various":[135],"Field":[136],"views":[138],"(FOV),":[139],"object":[140,146,174],"distances,":[141],"lighting":[142],"conditions,":[143],"color,":[144],"size.":[147],"Prior":[148],"research":[149],"has":[150],"demonstrated":[151],"can":[155],"reduce":[156],"reliance":[157],"extensive":[159],"annotations":[161],"improve":[163],"generalizability":[165],"vision":[167],"models.":[168],"Thus,":[169],"benchmark":[171],"several":[172],"state-of-the-art":[173],"models":[176],"demonstrate":[178,194],"introducing":[180],"improves":[183],"accuracy":[186],"generalization":[188],"conditions.":[191],"These":[192],"experiments":[193],"model":[203],"narrowing":[206],"Sim2Real":[208],"providing":[210],"valuable":[212],"foundation":[213],"developing":[215],"automated":[216],"systems":[219],"aviation":[221],"maintenance.":[222]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-12-03T00:00:00"}
