{"id":"https://openalex.org/W4214722339","doi":"https://doi.org/10.1145/3508546.3508616","title":"Dual Partial Recurrent Networks for Hyperspectral Image Change Detection","display_name":"Dual Partial Recurrent Networks for Hyperspectral Image Change Detection","publication_year":2021,"publication_date":"2021-12-22","ids":{"openalex":"https://openalex.org/W4214722339","doi":"https://doi.org/10.1145/3508546.3508616"},"language":"en","primary_location":{"id":"doi:10.1145/3508546.3508616","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3508546.3508616","pdf_url":null,"source":{"id":"https://openalex.org/S4363608505","display_name":"2021 4th International Conference on Algorithms, Computing and Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 4th International Conference on Algorithms, Computing and Artificial Intelligence","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/A5051381076","display_name":"Xiaochen Yuan","orcid":"https://orcid.org/0000-0002-7490-6695"},"institutions":[{"id":"https://openalex.org/I49835588","display_name":"Macao Polytechnic University","ror":"https://ror.org/02sf5td35","country_code":"MO","type":"education","lineage":["https://openalex.org/I49835588"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Xiaochen Yuan","raw_affiliation_strings":["School of Applied Sciences, Macao Polytechnic Institute, Macau"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Applied Sciences, Macao Polytechnic Institute, Macau","institution_ids":["https://openalex.org/I49835588"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100454981","display_name":"Jinlong Li","orcid":"https://orcid.org/0000-0002-5107-0362"},"institutions":[{"id":"https://openalex.org/I111950717","display_name":"Macau University of Science and Technology","ror":"https://ror.org/03jqs2n27","country_code":"MO","type":"education","lineage":["https://openalex.org/I111950717","https://openalex.org/I4391767947"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Jinlong Li","raw_affiliation_strings":["Faculty of Information Technology, Macau University of Science and Technology, Macau"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Macau University of Science and Technology, Macau","institution_ids":["https://openalex.org/I111950717"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3625,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59826947,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.984499990940094,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9521999955177307,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8651503324508667},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6526678800582886},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5778315663337708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5641153454780579},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5590612888336182},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4975176155567169},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37265080213546753}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8651503324508667},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6526678800582886},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5778315663337708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5641153454780579},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5590612888336182},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4975176155567169},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37265080213546753},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3508546.3508616","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3508546.3508616","pdf_url":null,"source":{"id":"https://openalex.org/S4363608505","display_name":"2021 4th International Conference on Algorithms, Computing and Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 4th International Conference on Algorithms, Computing and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1973965874","https://openalex.org/W1977180815","https://openalex.org/W1998595580","https://openalex.org/W2051103995","https://openalex.org/W2129265144","https://openalex.org/W2161160262","https://openalex.org/W2475443083","https://openalex.org/W2741377155","https://openalex.org/W2750976776","https://openalex.org/W2883305476","https://openalex.org/W2902788350","https://openalex.org/W2924390576","https://openalex.org/W2969663607","https://openalex.org/W3015038817","https://openalex.org/W3036453075","https://openalex.org/W3105553032"],"related_works":["https://openalex.org/W2783789044","https://openalex.org/W3211035526","https://openalex.org/W1869808405","https://openalex.org/W2028628118","https://openalex.org/W2031007444","https://openalex.org/W4291701050","https://openalex.org/W2775464024","https://openalex.org/W2972973180","https://openalex.org/W1491778359","https://openalex.org/W4293272463"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,31],"Dual":[4],"Partial":[5],"Recurrent":[6],"Networks":[7],"(DUAL-PRNs)":[8],"which":[9],"can":[10,82],"project":[11],"more":[12,73],"accurate":[13],"and":[14,65,79,100,115],"effective":[15],"image":[16],"features":[17,61,88,114],"by":[18,63,92],"learning":[19],"invariant":[20,38,59,78],"pixel":[21,39,60,69],"pairs":[22,40],"with":[23,41],"high":[24,42],"confidence.":[25],"The":[26],"Change":[27,119],"Vector":[28],"Analysis":[29,52],"provides":[30],"reference":[32],"for":[33],"the":[34,48,58,67,77,108,118,123,127,139,148],"model":[35,143,150],"to":[36,56,106],"select":[37],"confidence":[43],"as":[44],"training":[45],"samples.":[46],"Then,":[47],"Unsupervised":[49],"Slow":[50],"Feature":[51],"(USFA)":[53],"is":[54,104],"utilized":[55],"suppress":[57],"projected":[62],"DUAL-PRNs,":[64],"highlight":[66],"variant":[68,80],"features,":[70],"respectively.":[71],"Thus,":[72],"obvious":[74],"discrimination":[75],"between":[76,110],"pixels":[81],"be":[83],"achieved.":[84],"Two":[85],"groups":[86,112],"of":[87,113],"are":[89],"then":[90],"obtained":[91],"passing":[93],"bi-temporal":[94],"remote":[95],"sensing":[96],"images":[97],"through":[98],"DUAL-PRNs":[99,144],"USFA.":[101],"Chi-square":[102],"distance":[103],"employed":[105],"calculate":[107],"divergence":[109],"two":[111],"thus":[116],"generate":[117],"Intensity":[120],"Map.":[121],"Finally,":[122],"thresholding":[124],"algorithm":[125],"transforms":[126],"change":[128,133,141],"intensity":[129],"map":[130],"into":[131],"binary":[132],"map.":[134],"Experimental":[135],"results":[136],"show":[137],"that":[138],"proposed":[140],"detection":[142],"performs":[145],"better":[146],"than":[147],"advanced":[149],"DSFA-128-2.":[151]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}