{"id":"https://openalex.org/W4400771924","doi":"https://doi.org/10.1109/jstars.2024.3411670","title":"Land Cover Classification From Sentinel-2 Images With Quantum-Classical Convolutional Neural Networks","display_name":"Land Cover Classification From Sentinel-2 Images With Quantum-Classical Convolutional Neural Networks","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400771924","doi":"https://doi.org/10.1109/jstars.2024.3411670"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2024.3411670","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2024.3411670","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2024.3411670","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014303173","display_name":"Fan Fan","orcid":"https://orcid.org/0000-0002-5198-5239"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fan Fan","raw_affiliation_strings":["Chair of Data Science in Earth Observation, Technical University of Munich (TUM), Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0002-5198-5239","affiliations":[{"raw_affiliation_string":"Chair of Data Science in Earth Observation, Technical University of Munich (TUM), Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101142782","display_name":"Yi-Lei Shi","orcid":"https://orcid.org/0000-0003-1907-8214"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Yilei Shi","raw_affiliation_strings":["School of Engineering and Design, Technical University of Munich, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and Design, Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111015066","display_name":"Xiao Xiang Zhu","orcid":"https://orcid.org/0000-0001-8107-9096"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Xiao Xiang Zhu","raw_affiliation_strings":["Chair of Data Science in Earth Observation, Technical University of Munich (TUM), M&#x00FC;nchen, Germany"],"raw_orcid":"https://orcid.org/0000-0001-8107-9096","affiliations":[{"raw_affiliation_string":"Chair of Data Science in Earth Observation, Technical University of Munich (TUM), M&#x00FC;nchen, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I62916508"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":3.1199,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.92365301,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"17","issue":null,"first_page":"12477","last_page":"12489"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.998199999332428,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8189023733139038},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7178499698638916},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6959167718887329},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6015686392784119},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5887057781219482},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5778257250785828},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.5262305736541748},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4706308841705322},{"id":"https://openalex.org/keywords/quantum-computer","display_name":"Quantum computer","score":0.44646716117858887},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44105249643325806},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.4204959571361542},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3991783857345581},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3303503096103668},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.2990436553955078},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08485358953475952},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.07129201292991638}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8189023733139038},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7178499698638916},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6959167718887329},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6015686392784119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5887057781219482},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5778257250785828},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.5262305736541748},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4706308841705322},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.44646716117858887},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44105249643325806},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.4204959571361542},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3991783857345581},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3303503096103668},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.2990436553955078},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08485358953475952},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.07129201292991638},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2024.3411670","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2024.3411670","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6d1c83669ff54ad4a593a48073f9747a","is_oa":true,"landing_page_url":"https://doaj.org/article/6d1c83669ff54ad4a593a48073f9747a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 12477-12489 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2024.3411670","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2024.3411670","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5400000214576721,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[{"id":"https://openalex.org/F5395805803","display_name":"Munich Center for Machine Learning","ror":"https://ror.org/02nfy3535"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2001883788","https://openalex.org/W2030737358","https://openalex.org/W2063907334","https://openalex.org/W2261059368","https://openalex.org/W2275410481","https://openalex.org/W2399499800","https://openalex.org/W2725897987","https://openalex.org/W2940726923","https://openalex.org/W2949351478","https://openalex.org/W2990961515","https://openalex.org/W3007766931","https://openalex.org/W3010243192","https://openalex.org/W3022140654","https://openalex.org/W3037788579","https://openalex.org/W3085534640","https://openalex.org/W3101925575","https://openalex.org/W3131201603","https://openalex.org/W3131862063","https://openalex.org/W3134618813","https://openalex.org/W3179897198","https://openalex.org/W3201342863","https://openalex.org/W3201454638","https://openalex.org/W3207350910","https://openalex.org/W3214451036","https://openalex.org/W3215070584","https://openalex.org/W4212855986","https://openalex.org/W4285605423","https://openalex.org/W4291653280","https://openalex.org/W4305005880","https://openalex.org/W4309347615","https://openalex.org/W4312313149","https://openalex.org/W4315778447","https://openalex.org/W4322753249","https://openalex.org/W4386825310","https://openalex.org/W6631190155","https://openalex.org/W6774854366","https://openalex.org/W6845668075"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W4382618745","https://openalex.org/W1973775000","https://openalex.org/W4318664220","https://openalex.org/W2043913960","https://openalex.org/W3129683637"],"abstract_inverted_index":{"Exploiting":[0],"machine":[1,36],"learning":[2,37,79],"techniques":[3],"to":[4,27,54,88,161],"automatically":[5],"classify":[6],"multispectral":[7,93],"remote":[8],"sensing":[9],"imagery":[10],"plays":[11],"a":[12,52],"significant":[13],"role":[14],"in":[15,58,159],"deriving":[16],"changes":[17],"on":[18,64,108],"the":[19,23,59,109,113,138,162],"Earth\u2019s":[20],"surface.":[21],"However,":[22],"computation":[24],"power":[25],"required":[26],"manage":[28],"large":[29],"Earth":[30],"observation":[31],"data":[32],"and":[33,95,156,173],"apply":[34],"sophisticated":[35],"models":[38,84,126,145,169],"for":[39,98],"this":[40,56],"analysis":[41],"purpose":[42],"has":[43],"become":[44],"an":[45,149],"intractable":[46],"bottleneck.":[47],"Leveraging":[48],"quantum":[49,73,86],"computing":[50,87,97],"provides":[51],"possibility":[53],"tackle":[55],"challenge":[57],"future.":[60],"This":[61],"article":[62],"focuses":[63],"land":[65],"cover":[66],"classification":[67],"by":[68],"analyzing":[69],"Sentinel-2":[70],"images":[71,94],"with":[72,133,148],"computing.":[74],"Two":[75],"hybrid":[76],"quantum-classical":[77],"deep":[78],"frameworks":[80],"are":[81],"proposed.":[82],"Both":[83],"exploit":[85],"extract":[89,128],"features":[90,129],"efficiently":[91],"from":[92],"classical":[96,135],"final":[99],"classification.":[100],"As":[101],"proof":[102],"of":[103,154],"concept,":[104],"numerical":[105],"simulation":[106],"results":[107],"LCZ42":[110],"dataset":[111],"through":[112],"TensorFlow":[114],"Quantum":[115],"platform":[116],"verify":[117],"our":[118,125,167],"models'":[119],"validity.":[120],"The":[121],"experiments":[122],"indicate":[123],"that":[124],"can":[127],"more":[130],"effectively":[131],"compared":[132],"their":[134],"counterparts,":[136],"specifically,":[137],"convolutional":[139],"neural":[140],"network":[141],"(CNN)":[142],"model.":[143,164],"Our":[144],"demonstrated":[146],"improvements,":[147],"average":[150],"test":[151],"accuracy":[152],"increase":[153],"4.5%":[155],"3.3%,":[157],"respectively,":[158],"comparison":[160],"CNN":[163,176],"In":[165],"addition,":[166],"proposed":[168],"exhibit":[170],"better":[171],"transferability":[172],"robustness":[174],"than":[175],"models.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":10}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}
