{"id":"https://openalex.org/W7131125082","doi":"https://doi.org/10.1109/iccvw69036.2025.00152","title":"SynSpill: Improved Industrial Spill Detection with Synthetic Data","display_name":"SynSpill: Improved Industrial Spill Detection with Synthetic Data","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W7131125082","doi":"https://doi.org/10.1109/iccvw69036.2025.00152"},"language":null,"primary_location":{"id":"doi:10.1109/iccvw69036.2025.00152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2508.10171","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5097083737","display_name":"Aaditya Baranwal","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Aaditya Baranwal","raw_affiliation_strings":["University of Central Florida,Orlando,FL,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida,Orlando,FL,USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063683413","display_name":"Abdul Mueez","orcid":"https://orcid.org/0000-0002-7871-8632"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abdul Mueez","raw_affiliation_strings":["University of Central Florida,Orlando,FL,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida,Orlando,FL,USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126643518","display_name":"Jason Voelker","orcid":null},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jason Voelker","raw_affiliation_strings":["Siemens Energy,Orlando,FL,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Siemens Energy,Orlando,FL,USA","institution_ids":["https://openalex.org/I1325886976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108997445","display_name":"Guneet Singh Bhatia","orcid":null},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Guneet Bhatia","raw_affiliation_strings":["Siemens Energy,Orlando,FL,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Siemens Energy,Orlando,FL,USA","institution_ids":["https://openalex.org/I1325886976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125060219","display_name":"Shruti Vyas","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shruti Vyas","raw_affiliation_strings":["University of Central Florida,Orlando,FL,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida,Orlando,FL,USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5097083737"],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.84392628,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1425","last_page":"1434"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.16099999845027924,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.16099999845027924,"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/T11622","display_name":"Maritime Navigation and Safety","score":0.0575999990105629,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.03709999844431877,"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/synthetic-data","display_name":"Synthetic data","score":0.8413000106811523},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7301999926567078},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.5292999744415283},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5170999765396118},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.453900009393692},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.42969998717308044},{"id":"https://openalex.org/keywords/hazardous-waste","display_name":"Hazardous waste","score":0.36800000071525574}],"concepts":[{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.8413000106811523},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7301999926567078},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6241999864578247},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.5292999744415283},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5170999765396118},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42969998717308044},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37700000405311584},{"id":"https://openalex.org/C22507642","wikidata":"https://www.wikidata.org/wiki/Q1069369","display_name":"Hazardous waste","level":2,"score":0.36800000071525574},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3538999855518341},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3183000087738037},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.289900004863739},{"id":"https://openalex.org/C82753439","wikidata":"https://www.wikidata.org/wiki/Q1419090","display_name":"Industrial production","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.2728999853134155},{"id":"https://openalex.org/C110593043","wikidata":"https://www.wikidata.org/wiki/Q7300787","display_name":"Real-time data","level":2,"score":0.2632000148296356}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccvw69036.2025.00152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2508.10171","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2508.10171","pdf_url":"https://arxiv.org/pdf/2508.10171","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2508.10171","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2508.10171","pdf_url":"https://arxiv.org/pdf/2508.10171","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":[{"display_name":"Industry, innovation and infrastructure","score":0.46244654059410095,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7131125082.pdf","grobid_xml":"https://content.openalex.org/works/W7131125082.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2170140722","https://openalex.org/W2560647685","https://openalex.org/W3035574324","https://openalex.org/W3096609285","https://openalex.org/W3124432240","https://openalex.org/W3138516171","https://openalex.org/W3153675281","https://openalex.org/W3176828726","https://openalex.org/W3215947121","https://openalex.org/W4312497550","https://openalex.org/W4312651322","https://openalex.org/W4312761717","https://openalex.org/W4312933868","https://openalex.org/W4312956471","https://openalex.org/W4386072096","https://openalex.org/W4386076325","https://openalex.org/W4390873054","https://openalex.org/W4390874575","https://openalex.org/W4402669802","https://openalex.org/W4404789553","https://openalex.org/W4406258412","https://openalex.org/W4409434936"],"related_works":[],"abstract_inverted_index":{"Large-scale":[0],"Vision-Language":[1],"Models":[2],"(VLMs)":[3],"have":[4],"transformed":[5],"general-purpose":[6],"visual":[7],"recognition":[8],"through":[9],"strong":[10],"zero-shot":[11],"capabilities.":[12],"However,":[13],"their":[14,135],"performance":[15,93,136],"degrades":[16],"significantly":[17],"in":[18,104,156,176],"niche,":[19],"safety-critical":[20,157],"domains":[21],"such":[22,98],"as":[23,99],"industrial":[24,57,177],"spill":[25,118],"detection,":[26],"where":[27,179],"hazardous":[28],"events":[29],"are":[30],"rare,":[31],"sensitive,":[32],"and":[33,44,89,101,129,164],"difficult":[34],"to":[35,116,151,184],"annotate.":[36],"This":[37],"scarcity-driven":[38],"by":[39,63],"privacy":[40],"concerns,":[41],"data":[42,73,109,146,181],"sensitivity,":[43],"the":[45,92,105,153],"infrequency":[46],"of":[47,52,87,94,107,161],"real":[48,180],"incidents-renders":[49],"conventional":[50],"fine-tuning":[51],"detectors":[53,97,130],"infeasible":[54],"for":[55,172],"most":[56],"settings.":[58],"We":[59,76],"address":[60],"this":[61,79],"challenge":[62],"introducing":[64],"a":[65,70,143,148,168],"scalable":[66,170],"framework":[67],"centered":[68],"on":[69],"high-quality":[71],"synthetic":[72,80,108,145,162],"generation":[74,163],"pipeline.":[75],"demonstrate":[77],"that":[78,142],"corpus":[81],"enables":[82],"effective":[83],"Parameter-Efficient":[84],"Fine-Tuning":[85],"(PEFT)":[86],"VLMs":[88,112,128],"substantially":[90],"boosts":[91],"state-of-the-art":[95],"object":[96],"YOLO":[100],"DETR.":[102],"Notably,":[103],"absence":[106],"(SynSpill":[110],"dataset),":[111],"still":[113],"generalize":[114],"better":[115],"unseen":[117],"scenarios":[119],"than":[120],"these":[121],"detectors.":[122],"When":[123],"SynSpill":[124],"is":[125,147,182],"used,":[126],"both":[127],"achieve":[131],"marked":[132],"improvements,":[133],"with":[134],"becoming":[137],"comparable.":[138],"Our":[139],"results":[140],"underscore":[141],"high-fidelity":[144],"powerful":[149],"means":[150],"bridge":[152],"domain":[154],"gap":[155],"applications.":[158],"The":[159],"combination":[160],"lightweight":[165],"adaptation":[166],"offers":[167],"cost-effective,":[169],"pathway":[171],"deploying":[173],"vision":[174],"systems":[175],"environments":[178],"scarce/impractical":[183],"obtain.":[185],"Project":[186],"Page:":[187],"synspill.":[188],"vercel.app":[189]},"counts_by_year":[],"updated_date":"2026-04-26T08:31:28.666265","created_date":"2026-02-24T00:00:00"}