{"id":"https://openalex.org/W4416251964","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228730","title":"Temperature Inversion guided Attention for Infrared Small Target Detection","display_name":"Temperature Inversion guided Attention for Infrared Small Target Detection","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251964","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228730"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228730","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228730","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062948751","display_name":"Yuxiang Zhang","orcid":"https://orcid.org/0000-0002-3256-042X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxiang Zhang","raw_affiliation_strings":["Beijing University of Technology,College of Computer Science,Beijing,China,100124"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,College of Computer Science,Beijing,China,100124","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100458345","display_name":"Ting Zhang","orcid":"https://orcid.org/0009-0000-8254-5175"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Zhang","raw_affiliation_strings":["Beijing University of Technology,College of Computer Science,Beijing,China,100124"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,College of Computer Science,Beijing,China,100124","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109725535","display_name":"Zhaoying Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoying Liu","raw_affiliation_strings":["Beijing University of Technology,College of Computer Science,Beijing,China,100124"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,College of Computer Science,Beijing,China,100124","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115587783","display_name":"\u0411\u043e \u041b\u044e","orcid":"https://orcid.org/0000-0003-3045-628X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Liu","raw_affiliation_strings":["Beijing University of Technology,College of Computer Science,Beijing,China,100124"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Technology,College of Computer Science,Beijing,China,100124","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041589060","display_name":"Changming Sun","orcid":"https://orcid.org/0000-0001-5943-1989"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Changming Sun","raw_affiliation_strings":["CSIRO Data61,Epping,NSW,Australia,1710"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CSIRO Data61,Epping,NSW,Australia,1710","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I1292875679"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.853600025177002,"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"}},"topics":[{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.853600025177002,"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":0.03840000182390213,"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/T12994","display_name":"Infrared Thermography in Medicine","score":0.02199999988079071,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6259999871253967},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.5311999917030334},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.49970000982284546},{"id":"https://openalex.org/keywords/thermography","display_name":"Thermography","score":0.4699000120162964},{"id":"https://openalex.org/keywords/thermal-infrared","display_name":"Thermal infrared","score":0.45590001344680786},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.45579999685287476},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.43779999017715454},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42730000615119934},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.4065000116825104}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6259999871253967},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6036999821662903},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.5311999917030334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5231000185012817},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.49970000982284546},{"id":"https://openalex.org/C2779222261","wikidata":"https://www.wikidata.org/wiki/Q624587","display_name":"Thermography","level":3,"score":0.4699000120162964},{"id":"https://openalex.org/C2984335091","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Thermal infrared","level":3,"score":0.45590001344680786},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.45579999685287476},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.43779999017715454},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42730000615119934},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4065000116825104},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3596999943256378},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3549000024795532},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3474999964237213},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.34360000491142273},{"id":"https://openalex.org/C204530211","wikidata":"https://www.wikidata.org/wiki/Q752823","display_name":"Thermal","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C72293138","wikidata":"https://www.wikidata.org/wiki/Q909741","display_name":"Temperature measurement","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3091999888420105},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C2779067591","wikidata":"https://www.wikidata.org/wiki/Q3628987","display_name":"Atmospheric Infrared Sounder","level":3,"score":0.2800999879837036},{"id":"https://openalex.org/C2776445388","wikidata":"https://www.wikidata.org/wiki/Q6716998","display_name":"MODTRAN","level":3,"score":0.2759999930858612},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.2596000134944916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228730","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228730","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321793","display_name":"Beijing Municipal Education Commission","ror":"https://ror.org/04bpn6s66"},{"id":"https://openalex.org/F4320321913","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1965737830","https://openalex.org/W1978993121","https://openalex.org/W1988122332","https://openalex.org/W1992873714","https://openalex.org/W2001564322","https://openalex.org/W2041560658","https://openalex.org/W2057390839","https://openalex.org/W2058529145","https://openalex.org/W2067542652","https://openalex.org/W2103541076","https://openalex.org/W2117675177","https://openalex.org/W2407220925","https://openalex.org/W2578504242","https://openalex.org/W2774244034","https://openalex.org/W2991758591","https://openalex.org/W3039443125","https://openalex.org/W3118249006","https://openalex.org/W3118934234","https://openalex.org/W3124866053","https://openalex.org/W3131385700","https://openalex.org/W3138516171","https://openalex.org/W3160822809","https://openalex.org/W3206023204","https://openalex.org/W3211490618","https://openalex.org/W4210718980","https://openalex.org/W4312827004","https://openalex.org/W4313065862","https://openalex.org/W4313506322","https://openalex.org/W4313855947","https://openalex.org/W4386737385","https://openalex.org/W4387951721","https://openalex.org/W4391376377","https://openalex.org/W4401415788","https://openalex.org/W4402353259","https://openalex.org/W4403977303","https://openalex.org/W4405786284","https://openalex.org/W4406457610"],"related_works":[],"abstract_inverted_index":{"Targets":[0],"in":[1,30,54,66,108],"infrared":[2,15,67,126],"images":[3],"typically":[4],"lack":[5],"distinct":[6],"texture":[7],"and":[8,34,145,173,187,202,214],"color":[9],"features,":[10],"posing":[11],"significant":[12],"challenges":[13],"for":[14],"small":[16,188],"target":[17,99],"detection.":[18],"Although":[19],"existing":[20],"methods":[21,48],"have":[22,28],"made":[23],"some":[24],"progress,":[25],"they":[26],"still":[27],"limitations":[29],"terms":[31],"of":[32,125,136,185,234],"interpretability":[33],"are":[35],"unable":[36],"to":[37,42,59,93,128,154,228],"provide":[38],"sufficient":[39],"theoretical":[40],"grounds":[41],"explain":[43],"their":[44],"effectiveness.":[45],"Moreover,":[46],"these":[47],"generally":[49],"overlook":[50],"the":[51,55,62,91,98,104,122,130,141,183],"temperature":[52,87,105,115,131,175],"information":[53],"imaging":[56,127],"process,":[57],"failing":[58],"fully":[60],"exploit":[61],"subtle":[63],"thermal":[64],"differences":[65],"images,":[68],"which":[69,120],"consequently":[70],"limits":[71],"detection":[72,212],"accuracy.":[73],"To":[74],"this":[75],"end,":[76],"we":[77,111],"propose":[78,112],"a":[79,113,156],"novel":[80],"temperature-aware":[81,162],"Transformer":[82,153,163],"network":[83],"(TATransNet).":[84],"By":[85,166],"introducing":[86],"information,":[88],"it":[89],"allows":[90],"model":[92],"be":[94,178],"more":[95],"focused":[96],"on":[97,193],"area.":[100],"Specifically,":[101],"inspired":[102],"by":[103],"inversion":[106,116],"technique":[107],"remote":[109],"sensing,":[110],"learnable":[114],"attention":[117],"module":[118],"(TIAM),":[119],"simulates":[121],"inverse":[123],"process":[124],"perceive":[129],"distribution":[132],"across":[133],"feature":[134],"maps":[135],"different":[137,232],"scales,":[138],"thereby":[139,181],"enhancing":[140],"distinguishability":[142],"between":[143],"foreground":[144],"background.":[146],"We":[147],"further":[148],"integrate":[149],"TIAM":[150],"with":[151,231],"Swin":[152],"construct":[155],"Transformer-CNN":[157],"hybrid":[158],"encoder":[159],"unit,":[160],"termed":[161],"block":[164],"(TATB).":[165],"stacking":[167],"multiple":[168],"TATBs,":[169],"both":[170],"global":[171],"context":[172],"local":[174],"features":[176],"can":[177],"captured":[179],"simultaneously,":[180],"strengthening":[182],"representation":[184],"dim":[186],"targets":[189],"effectively.":[190],"Experimental":[191],"results":[192],"five":[194],"benchmark":[195],"datasets,":[196],"i.e.,":[197],"Small-ExtIRShip,":[198],"Small-SSDD,":[199],"NUAA-SIRST,":[200],"IRSTD-1K,":[201],"IHAST":[203],"demonstrate":[204],"that":[205],"our":[206],"method":[207],"not":[208],"only":[209],"significantly":[210],"improves":[211],"accuracy":[213],"reduces":[215],"false":[216],"alarm":[217],"rates,":[218],"but":[219],"also":[220],"demonstrates":[221],"strong":[222],"generalization":[223],"capability,":[224],"enabling":[225],"effective":[226],"transfer":[227],"other":[229],"approaches":[230],"types":[233],"encoders.":[235]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}