{"id":"https://openalex.org/W3162950802","doi":"https://doi.org/10.1109/icpr48806.2021.9412293","title":"A Dual-Branch Network for Infrared and Visible Image Fusion","display_name":"A Dual-Branch Network for Infrared and Visible Image Fusion","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3162950802","doi":"https://doi.org/10.1109/icpr48806.2021.9412293","mag":"3162950802"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412293","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5006506263","display_name":"Yu Fu","orcid":"https://orcid.org/0000-0002-5632-8158"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Fu","raw_affiliation_strings":["Jiangsu Provincial Engineering, Laboratory of Pattern Recognition and Computational Intelligence, Jiangnan University,Wuxi,China,214122"],"affiliations":[{"raw_affiliation_string":"Jiangsu Provincial Engineering, Laboratory of Pattern Recognition and Computational Intelligence, Jiangnan University,Wuxi,China,214122","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087450445","display_name":"Xiao\u2010Jun Wu","orcid":"https://orcid.org/0000-0002-0310-5778"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao-Jun Wu","raw_affiliation_strings":["Jiangsu Provincial Engineering, Laboratory of Pattern Recognition and Computational Intelligence, Jiangnan University,Wuxi,China,214122"],"affiliations":[{"raw_affiliation_string":"Jiangsu Provincial Engineering, Laboratory of Pattern Recognition and Computational Intelligence, Jiangnan University,Wuxi,China,214122","institution_ids":["https://openalex.org/I111599522"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006506263"],"corresponding_institution_ids":["https://openalex.org/I111599522"],"apc_list":null,"apc_paid":null,"fwci":8.1918,"has_fulltext":false,"cited_by_count":82,"citation_normalized_percentile":{"value":0.97886276,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"10675","last_page":"10680"},"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":0.9975000023841858,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9972000122070312,"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/autoencoder","display_name":"Autoencoder","score":0.793835461139679},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7284058332443237},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7105743885040283},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6740955114364624},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6580639481544495},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6372137665748596},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.6318001747131348},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.595634937286377},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5285478830337524},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5000607967376709},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4564433693885803},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4413120448589325}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.793835461139679},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7284058332443237},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7105743885040283},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6740955114364624},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6580639481544495},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6372137665748596},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.6318001747131348},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.595634937286377},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5285478830337524},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5000607967376709},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4564433693885803},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4413120448589325},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412293","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412293","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1628236353","https://openalex.org/W1964641132","https://openalex.org/W1965606870","https://openalex.org/W1969147977","https://openalex.org/W1980382026","https://openalex.org/W1997596006","https://openalex.org/W1998393535","https://openalex.org/W2020442368","https://openalex.org/W2026651590","https://openalex.org/W2035848186","https://openalex.org/W2036485827","https://openalex.org/W2082232962","https://openalex.org/W2091484864","https://openalex.org/W2103504761","https://openalex.org/W2133665775","https://openalex.org/W2143696753","https://openalex.org/W2153777140","https://openalex.org/W2221102299","https://openalex.org/W2266694576","https://openalex.org/W2331128040","https://openalex.org/W2474462684","https://openalex.org/W2559870345","https://openalex.org/W2744070429","https://openalex.org/W2767512561","https://openalex.org/W2798987894","https://openalex.org/W2912147220","https://openalex.org/W2947275790","https://openalex.org/W2963446712","https://openalex.org/W2963530785","https://openalex.org/W2964121744","https://openalex.org/W2969937244","https://openalex.org/W3007891240","https://openalex.org/W3105639468","https://openalex.org/W6631190155","https://openalex.org/W6702130928","https://openalex.org/W6766837696","https://openalex.org/W6864450276"],"related_works":["https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2139242969","https://openalex.org/W2284201331","https://openalex.org/W2095903272"],"abstract_inverted_index":{"In":[0,15],"recent":[1],"years,":[2],"deep":[3,37],"learning":[4,38],"has":[5,50],"been":[6],"used":[7],"extensively":[8],"in":[9,46],"the":[10,48,64,89,94,105],"field":[11],"of":[12,80],"image":[13,22,106],"fusion.":[14],"this":[16],"article,":[17],"we":[18],"propose":[19],"a":[20,27,31,36,51,99],"new":[21,28,32,100],"fusion":[23,75,90],"method":[24,113],"by":[25],"designing":[26],"structure":[29],"and":[30,59,70],"loss":[33,101],"function":[34,102],"for":[35],"model.":[39],"Our":[40],"backbone":[41],"network":[42],"is":[43],"an":[44],"autoencoder,":[45],"which":[47],"encoder":[49,65],"dual":[52],"branch":[53],"structure.":[54],"We":[55,97],"input":[56],"infrared":[57],"images":[58,62],"visible":[60],"light":[61],"to":[63,66,82,92,103],"extract":[67],"detailed":[68],"information":[69,72],"semantic":[71],"respectively.":[73],"The":[74,86],"layer":[76],"fuses":[77],"two":[78],"sets":[79],"features":[81,91],"get":[83],"fused":[84,95],"features.":[85],"decoder":[87],"reconstructs":[88],"obtain":[93],"image.":[96],"design":[98],"reconstruct":[104],"effectively.":[107],"Experiments":[108],"show":[109],"that":[110],"our":[111],"proposed":[112],"achieves":[114],"state-of-the-art":[115],"performance.":[116]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
