{"id":"https://openalex.org/W7141462741","doi":"https://doi.org/10.48550/arxiv.2603.25170","title":"Knowledge-Guided Adversarial Training for Infrared Object Detection via Thermal Radiation Modeling","display_name":"Knowledge-Guided Adversarial Training for Infrared Object Detection via Thermal Radiation Modeling","publication_year":2026,"publication_date":"2026-03-26","ids":{"openalex":"https://openalex.org/W7141462741","doi":"https://doi.org/10.48550/arxiv.2603.25170"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.25170","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25170","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.25170","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130750385","display_name":"Shiji Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Shiji","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130816052","display_name":"Shukun Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Shukun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045992045","display_name":"Maoxun Yuan","orcid":"https://orcid.org/0000-0001-7463-7328"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Maoxun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130743782","display_name":"Yao Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Yao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130725734","display_name":"Ranjie Duan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duan, Ranjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130776418","display_name":"Qing Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Qing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130730525","display_name":"Jiansheng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jiansheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047387479","display_name":"Haibin Duan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duan, Haibin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130803524","display_name":"Xingxing Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Xingxing","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":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.398499995470047,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.398499995470047,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.16930000483989716,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10036","display_name":"Advanced Neural Network Applications","score":0.0860000029206276,"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/adversarial-system","display_name":"Adversarial system","score":0.7882000207901001},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.7318000197410583},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6687999963760376},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.572700023651123},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.45899999141693115},{"id":"https://openalex.org/keywords/thermal","display_name":"Thermal","score":0.3763999938964844},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.31619998812675476}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7882000207901001},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.7318000197410583},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6687999963760376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6383000016212463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5751000046730042},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.572700023651123},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45899999141693115},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42239999771118164},{"id":"https://openalex.org/C204530211","wikidata":"https://www.wikidata.org/wiki/Q752823","display_name":"Thermal","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C89394759","wikidata":"https://www.wikidata.org/wiki/Q192593","display_name":"Thermal radiation","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C2984335091","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Thermal infrared","level":3,"score":0.303600013256073},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2922999858856201},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C153385146","wikidata":"https://www.wikidata.org/wiki/Q18335","display_name":"Radiation","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C189645446","wikidata":"https://www.wikidata.org/wiki/Q350865","display_name":"Mirroring","level":2,"score":0.26269999146461487}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.25170","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25170","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":"doi:10.48550/arxiv.2603.25170","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25170","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.8046156167984009}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,71],"complex":[1,99],"environments,":[2],"infrared":[3,15,37,65,76,149,154,182,187],"object":[4,16,38,150,188],"detection":[5,17,189],"exhibits":[6],"broad":[7],"applicability":[8],"and":[9,24,79,104,125,164,184,199,204],"stability":[10,129],"across":[11],"diverse":[12],"scenarios.":[13],"However,":[14],"is":[18,157],"vulnerable":[19],"to":[20,28,53,170],"both":[21,196],"common":[22,105,205],"corruptions":[23],"adversarial":[25,102,161,202],"examples,":[26],"leading":[27],"potential":[29],"security":[30],"risks.":[31],"To":[32],"improve":[33],"the":[34,51,55,61,98,116,128,138,160,165,174],"robustness":[35,200],"of":[36,64,101,119,130],"detection,":[39,151],"current":[40],"methods":[41],"mostly":[42],"adopt":[43],"a":[44,93],"data-driven":[45],"ideology,":[46],"which":[47,153],"only":[48],"superficially":[49],"drives":[50],"network":[52],"fit":[54],"training":[56,162],"data":[57],"without":[58],"specifically":[59],"considering":[60],"unique":[62],"characteristics":[63],"images,":[66],"resulting":[67],"in":[68,152],"limited":[69],"robustness.":[70],"this":[72],"paper,":[73],"we":[74,108,142],"revisit":[75],"physical":[77,155,176],"knowledge":[78,95,156],"find":[80],"that":[81,192],"relative":[82],"thermal":[83,111,133],"radiation":[84,112,134],"relations":[85,113],"between":[86],"different":[87,123],"classes":[88],"can":[89],"be":[90,171],"regarded":[91],"as":[92],"reliable":[94],"source":[96],"under":[97],"scenarios":[100],"examples":[103],"corruptions.":[106,206],"Thus,":[107],"theoretically":[109],"model":[110],"based":[114],"on":[115,137,180],"rank":[117],"order":[118],"gray":[120],"values":[121],"for":[122,148],"classes,":[124],"further":[126],"quantify":[127],"various":[131],"inter-class":[132],"relations.":[135],"Based":[136],"above":[139],"theoretical":[140],"framework,":[141],"propose":[143],"Knowledge-Guided":[144],"Adversarial":[145],"Training":[146],"(KGAT)":[147],"embedded":[158],"into":[159],"process,":[163],"predicted":[166],"results":[167],"are":[168],"optimized":[169],"consistent":[172],"with":[173],"actual":[175],"laws.":[177],"Extensive":[178],"experiments":[179],"three":[181],"datasets":[183],"six":[185],"mainstream":[186],"models":[190],"demonstrate":[191],"KGAT":[193],"effectively":[194],"enhances":[195],"clean":[197],"accuracy":[198],"against":[201],"attacks":[203]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-28T00:00:00"}