{"id":"https://openalex.org/W4387828925","doi":"https://doi.org/10.1109/igarss52108.2023.10282010","title":"Deep Continuous Matching Network for more Robust Multi-Modal Remote Sensing Image Patch Matching","display_name":"Deep Continuous Matching Network for more Robust Multi-Modal Remote Sensing Image Patch Matching","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387828925","doi":"https://doi.org/10.1109/igarss52108.2023.10282010"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10282010","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282010","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","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/A5111060894","display_name":"Rufan Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rufan Zhou","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Xi’an,China,710071"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Xi’an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085893076","display_name":"Dou Quan","orcid":"https://orcid.org/0000-0001-6943-4657"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dou Quan","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Xi’an,China,710071"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Xi’an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042003236","display_name":"Chonghua Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chonghua Lv","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Xi’an,China,710071"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Xi’an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040240404","display_name":"Yanhe Guo","orcid":"https://orcid.org/0009-0003-6144-5070"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhe Guo","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Xi’an,China,710071"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Xi’an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065660222","display_name":"Shuang Wang","orcid":"https://orcid.org/0000-0003-4940-1211"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Wang","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Xi’an,China,710071"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Xi’an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100749025","display_name":"Yu Gu","orcid":"https://orcid.org/0000-0003-3634-2275"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Gu","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Xi’an,China,710071"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Xi’an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050630882","display_name":"Licheng Jiao","orcid":"https://orcid.org/0000-0003-3354-9617"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Licheng Jiao","raw_affiliation_strings":["Xidian University,School of Artificial Intelligence,Xi’an,China,710071"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,School of Artificial Intelligence,Xi’an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827"],"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":"30","issue":null,"first_page":"6057","last_page":"6060"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9947999715805054,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9944999814033508,"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/modal","display_name":"Modal","score":0.7849248647689819},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7499185800552368},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6775833964347839},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.6454300880432129},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5673345923423767},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5637994408607483},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5499802827835083},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5267084240913391},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5088706016540527},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.47387003898620605},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4704519808292389},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43666428327560425},{"id":"https://openalex.org/keywords/image-matching","display_name":"Image matching","score":0.42176881432533264},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3167470693588257},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19466233253479004}],"concepts":[{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7849248647689819},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7499185800552368},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6775833964347839},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.6454300880432129},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5673345923423767},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5637994408607483},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5499802827835083},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5267084240913391},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5088706016540527},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.47387003898620605},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4704519808292389},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43666428327560425},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.42176881432533264},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3167470693588257},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19466233253479004},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10282010","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282010","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","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/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2079700955","https://openalex.org/W2560647685","https://openalex.org/W2737260104","https://openalex.org/W2973660294","https://openalex.org/W3134976640","https://openalex.org/W3160949890","https://openalex.org/W4251502478","https://openalex.org/W6795124664"],"related_works":["https://openalex.org/W2385859805","https://openalex.org/W2530972254","https://openalex.org/W2374013449","https://openalex.org/W73545470","https://openalex.org/W2364381299","https://openalex.org/W2374430585","https://openalex.org/W3144423903","https://openalex.org/W627697492","https://openalex.org/W2317392152","https://openalex.org/W1528212084"],"abstract_inverted_index":{"Due":[0],"to":[1,102],"the":[2,29,35,45,50,58,61,68,76,80,131,137,143,149,157],"powerful":[3],"feature":[4],"extraction":[5],"capabilities":[6],"of":[7,60,79,139,153,162],"deep":[8,17,30,46,87],"neural":[9],"networks,":[10],"traditional":[11],"approaches":[12,19],"are":[13],"gradually":[14],"replaced":[15],"by":[16],"learning":[18,98,101,111,133],"for":[20,67,110,123,142],"image":[21,26,91,116,125],"matching":[22,92,127],"tasks.":[23],"For":[24,38],"multi-modal":[25,39,88,115,124],"patch":[27,117,126],"matching,":[28],"model":[31,47,64],"should":[32,48],"mainly":[33],"learn":[34,49],"modality-invariant":[36,51,112,144],"features.":[37,163],"images":[40],"with":[41,128],"rotation":[42],"transformation":[43],"(RT),":[44],"features":[52,55,81,113,145],"and":[53,99,151],"rotation-invariant":[54],"simultaneously.":[56],"However,":[57],"performance":[59],"latter":[62],"trained":[63,109],"is":[65,74,108,121],"degraded":[66],"former":[69],"task.":[70],"The":[71],"main":[72],"reason":[73],"that":[75,95],"modality":[77],"invariance":[78,159],"degenerates.":[82],"This":[83],"paper":[84],"proposes":[85],"a":[86],"remote":[89],"sensing":[90],"network":[93],"(DCMNet)":[94],"combines":[96],"descriptor":[97],"continuous":[100],"solve":[103],"this":[104],"problem.":[105],"Firstly,":[106],"DCMNet":[107,120,154],"in":[114,155],"matching.":[118],"Then,":[119],"optimized":[122],"RT.":[129],"In":[130],"later":[132],"process,":[134],"we":[135],"reduce":[136],"change":[138],"important":[140],"parameters":[141],"learning.":[146],"Experiments":[147],"demonstrate":[148],"effectiveness":[150],"robustness":[152],"alleviating":[156],"modal":[158],"degradation":[160],"problem":[161]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}