{"id":"https://openalex.org/W3171583161","doi":"https://doi.org/10.1145/3447587.3447603","title":"A New Infrared and Visible Image Fusion Method Based on Generative Adversarial Networks and Attention Mechanism","display_name":"A New Infrared and Visible Image Fusion Method Based on Generative Adversarial Networks and Attention Mechanism","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3171583161","doi":"https://doi.org/10.1145/3447587.3447603","mag":"3171583161"},"language":"en","primary_location":{"id":"doi:10.1145/3447587.3447603","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447587.3447603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 4th International Conference on Image and Graphics Processing","raw_type":"proceedings-article"},"type":"article","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/A5101959159","display_name":"Jixiao Wang","orcid":"https://orcid.org/0000-0003-3468-0721"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jixiao Wang","raw_affiliation_strings":["Command & Control Engineering College Army Engineering University of PLA, China"],"affiliations":[{"raw_affiliation_string":"Command & Control Engineering College Army Engineering University of PLA, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447990","display_name":"Yang Li","orcid":"https://orcid.org/0000-0003-1682-0284"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["Command & Control Engineering College Army Engineering University of PLA, China"],"affiliations":[{"raw_affiliation_string":"Command & Control Engineering College Army Engineering University of PLA, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100376489","display_name":"Zhuang Miao","orcid":"https://orcid.org/0000-0003-2289-4589"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuang Miao","raw_affiliation_strings":["Command & Control Engineering College Army Engineering University of PLA, China"],"affiliations":[{"raw_affiliation_string":"Command & Control Engineering College Army Engineering University of PLA, China","institution_ids":["https://openalex.org/I4210163363"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101959159"],"corresponding_institution_ids":["https://openalex.org/I4210163363"],"apc_list":null,"apc_paid":null,"fwci":0.2493,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5689426,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"109","last_page":"119"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9883999824523926,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7924382090568542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6885050535202026},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6543660163879395},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6430070996284485},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6134586334228516},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5480111837387085},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5307362675666809},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48045700788497925},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.46660277247428894},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.46183159947395325},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4596327245235443},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4558831453323364},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45543986558914185},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.42840877175331116},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3555607497692108},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35166803002357483},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3447275459766388},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08748272061347961}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7924382090568542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6885050535202026},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6543660163879395},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6430070996284485},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6134586334228516},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5480111837387085},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5307362675666809},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48045700788497925},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.46660277247428894},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.46183159947395325},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4596327245235443},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4558831453323364},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45543986558914185},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.42840877175331116},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3555607497692108},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35166803002357483},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3447275459766388},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08748272061347961},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447587.3447603","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447587.3447603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 4th International Conference on Image and Graphics Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5094434050","display_name":null,"funder_award_id":"61806220","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1708141795","https://openalex.org/W1902237438","https://openalex.org/W1964641132","https://openalex.org/W1965606870","https://openalex.org/W1969147977","https://openalex.org/W1997596006","https://openalex.org/W2026651590","https://openalex.org/W2038843149","https://openalex.org/W2040833130","https://openalex.org/W2103504761","https://openalex.org/W2133564696","https://openalex.org/W2266694576","https://openalex.org/W2286929393","https://openalex.org/W2410303706","https://openalex.org/W2558799462","https://openalex.org/W2559655401","https://openalex.org/W2559870345","https://openalex.org/W2579318141","https://openalex.org/W2589745805","https://openalex.org/W2610070095","https://openalex.org/W2736883612","https://openalex.org/W2751011928","https://openalex.org/W2752782242","https://openalex.org/W2754586843","https://openalex.org/W2767512561","https://openalex.org/W2773003563","https://openalex.org/W2798018774","https://openalex.org/W2809216229","https://openalex.org/W2809795042","https://openalex.org/W2912147220","https://openalex.org/W2955058313","https://openalex.org/W2963091558","https://openalex.org/W2963530785","https://openalex.org/W2963840672","https://openalex.org/W2964189376","https://openalex.org/W2999972022","https://openalex.org/W3102515681","https://openalex.org/W6746034047","https://openalex.org/W6748666111"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W3156786002","https://openalex.org/W2738221750","https://openalex.org/W4312831135","https://openalex.org/W4311257506","https://openalex.org/W2732542196","https://openalex.org/W564581980","https://openalex.org/W2337926734","https://openalex.org/W2550196753","https://openalex.org/W3129634582"],"abstract_inverted_index":{"With":[0],"various":[1],"attention":[2,9,27,52,72,78,81,157],"mechanisms":[3,10,53,73],"were":[4],"proposed,":[5],"the":[6,12,26,35,40,43,58,85,93,96,100,113,119,123,129,136,143,146,152,155,159,169,179,182],"application":[7],"of":[8,42,71,88,95,142,181],"in":[11],"different":[13,61],"deep":[14],"learning":[15],"tasks":[16],"has":[17],"occurred.":[18],"Meanwhile,":[19],"most":[20],"practices":[21],"and":[22,38,79,105,139,164,185,189],"experiments":[23],"demonstrate":[24],"that":[25,174],"mechanism":[28],"can":[29,134,177],"help":[30],"convolutional":[31,102,137],"networks":[32,104,108],"to":[33,56,82],"capture":[34],"critical":[36],"features":[37],"raise":[39],"performance":[41,94],"CNNs.":[44],"In":[45,63],"image":[46,89,166,184],"fusion":[47,90],"field,":[48],"few":[49],"methods":[50],"including":[51],"are":[54,75],"used":[55,127],"integrate":[57],"images":[59],"containing":[60],"modalities.":[62],"this":[64],"paper,":[65],"so,":[66],"we":[67],"utilize":[68],"three":[69],"types":[70],"which":[74],"self-attention,":[76],"dual":[77],"multi-scale":[80,156],"add":[83],"into":[84,128],"basic":[86,120,130],"network":[87,131],"for":[91,162],"developing":[92],"fused":[97,183],"images.":[98],"Since":[99],"traditional":[101],"neural":[103],"generative":[106],"adversarial":[107],"(GAN)":[109],"have":[110],"some":[111],"shortcomings,":[112],"modified":[114],"GAN":[115],"is":[116,126,158],"treated":[117],"as":[118],"network.":[121],"Besides,":[122],"dilated":[124],"convolution":[125],"because":[132],"it":[133],"enlarge":[135],"map":[138],"receptive":[140],"field":[141],"kernels":[144],"under":[145],"same":[147],"kernel":[148],"size":[149],"condition.":[150],"By":[151],"experimental":[153,171],"comparison,":[154],"best":[160],"practice":[161],"infrared":[163],"visible":[165],"fusion.":[167],"And":[168],"extensive":[170],"results":[172],"show":[173],"our":[175],"method":[176],"enhance":[178],"contrast":[180],"preserve":[186],"more":[187],"thermal":[188],"detail":[190],"information.":[191]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}