{"id":"https://openalex.org/W4375928796","doi":"https://doi.org/10.1109/tgrs.2023.3274355","title":"HyperQUEEN: Hyperspectral Quantum Deep Network For Image Restoration","display_name":"HyperQUEEN: Hyperspectral Quantum Deep Network For Image Restoration","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4375928796","doi":"https://doi.org/10.1109/tgrs.2023.3274355"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3274355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3274355","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5000566608","display_name":"Chia-Hsiang Lin","orcid":"https://orcid.org/0000-0002-4865-2329"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chia-Hsiang Lin","raw_affiliation_strings":["Department of Electrical Engineering and the Miin Wu School of Computing, National Cheng Kung University, Tainan, Taiwan","Department of Electrical Engineering, and with the Miin Wu School of Computing, National Cheng Kung University, Tainan, Taiwan (R.O.C.)"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and the Miin Wu School of Computing, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]},{"raw_affiliation_string":"Department of Electrical Engineering, and with the Miin Wu School of Computing, National Cheng Kung University, Tainan, Taiwan (R.O.C.)","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090760918","display_name":"Y. N. Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"You-Yao Chen","raw_affiliation_strings":["Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan (R.O.C.)"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan (R.O.C.)","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000566608"],"corresponding_institution_ids":["https://openalex.org/I91807558"],"apc_list":null,"apc_paid":null,"fwci":3.7094,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.9381318,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9973000288009644,"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":0.9973000288009644,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9930999875068665,"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/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8525820970535278},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5993635654449463},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.5174735188484192},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5089724063873291},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4498424530029297},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44110044836997986},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4282046854496002},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3455425500869751},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3240028917789459},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2983969449996948}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8525820970535278},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5993635654449463},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5174735188484192},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5089724063873291},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4498424530029297},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44110044836997986},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4282046854496002},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3455425500869751},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3240028917789459},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2983969449996948}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3274355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3274355","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320324663","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":87,"referenced_works":["https://openalex.org/W4132937","https://openalex.org/W1522301498","https://openalex.org/W1563049925","https://openalex.org/W1821462560","https://openalex.org/W1901129140","https://openalex.org/W1975366306","https://openalex.org/W1977824599","https://openalex.org/W1986909036","https://openalex.org/W2020918964","https://openalex.org/W2026302893","https://openalex.org/W2052725731","https://openalex.org/W2056370875","https://openalex.org/W2058803973","https://openalex.org/W2063790512","https://openalex.org/W2070424424","https://openalex.org/W2122374500","https://openalex.org/W2133665775","https://openalex.org/W2137147061","https://openalex.org/W2148132004","https://openalex.org/W2170608991","https://openalex.org/W2171845746","https://openalex.org/W2194775991","https://openalex.org/W2245855345","https://openalex.org/W2257979135","https://openalex.org/W2345286725","https://openalex.org/W2573722252","https://openalex.org/W2761752711","https://openalex.org/W2768345624","https://openalex.org/W2773752798","https://openalex.org/W2781738013","https://openalex.org/W2790888198","https://openalex.org/W2794444783","https://openalex.org/W2888774813","https://openalex.org/W2906538035","https://openalex.org/W2907987172","https://openalex.org/W2963239445","https://openalex.org/W2964085075","https://openalex.org/W2964257934","https://openalex.org/W2996446969","https://openalex.org/W2997865025","https://openalex.org/W2998841120","https://openalex.org/W3035035250","https://openalex.org/W3039247891","https://openalex.org/W3040152568","https://openalex.org/W3096831136","https://openalex.org/W3099200606","https://openalex.org/W3100122058","https://openalex.org/W3100931082","https://openalex.org/W3102507295","https://openalex.org/W3104396616","https://openalex.org/W3128589329","https://openalex.org/W3136502865","https://openalex.org/W3139898386","https://openalex.org/W3156898029","https://openalex.org/W3161932608","https://openalex.org/W3202984956","https://openalex.org/W3217784149","https://openalex.org/W4200380623","https://openalex.org/W4206163887","https://openalex.org/W4233760599","https://openalex.org/W4242275969","https://openalex.org/W4248694960","https://openalex.org/W4250658187","https://openalex.org/W4281891658","https://openalex.org/W4285181488","https://openalex.org/W4285264942","https://openalex.org/W4289606390","https://openalex.org/W4295312788","https://openalex.org/W4297102734","https://openalex.org/W4302888899","https://openalex.org/W4308005572","https://openalex.org/W4313168201","https://openalex.org/W4319586141","https://openalex.org/W4321194978","https://openalex.org/W6631190155","https://openalex.org/W6633544067","https://openalex.org/W6638523607","https://openalex.org/W6639824700","https://openalex.org/W6685078114","https://openalex.org/W6731905757","https://openalex.org/W6755964158","https://openalex.org/W6766978945","https://openalex.org/W6779681028","https://openalex.org/W6792262171","https://openalex.org/W6802304192","https://openalex.org/W6846331228","https://openalex.org/W6850304139"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W2385371209","https://openalex.org/W4250051149","https://openalex.org/W2083270190","https://openalex.org/W2974904990","https://openalex.org/W2365681766","https://openalex.org/W2393963626"],"abstract_inverted_index":{"Quantum":[0],"science":[1],"just":[2,104],"winning":[3],"the":[4,20,31,55,64,68,78,119,131,139,142,149,154,158,178,183,210,223],"2022":[5],"Nobel":[6],"Prize":[7],"in":[8,30],"Physics":[9],"must":[10],"lead":[11],"future":[12],"development":[13],"of":[14,24,67,146,212],"remote":[15,215],"sensing":[16],"technologies.":[17],"However,":[18],"given":[19],"very":[21,123],"limited":[22],"number":[23],"entangled":[25],"quantum":[26,34,49,56,65,94,113,160,185,213,225],"bits":[27],"(qubits)":[28],"even":[29],"most":[32],"advanced":[33],"computers,":[35],"is":[36,87,157],"processing":[37,96],"remotely":[38],"sensed":[39],"hyperspectral":[40,112,120,171,214],"image":[41,57,70,95,144],"(featured":[42],"by":[43],"its":[44,196],"large":[45],"data":[46],"volume)":[47],"using":[48,122],"computer":[50],"technically":[51],"feasible?":[52],"Even":[53],"if":[54],"state":[58,66],"can":[59,98],"be":[60,74,234],"well":[61,127],"processed":[62],"to":[63,82,90,117,129,141,166,193],"target":[69,143],"(QSTI),":[71],"it":[72,86],"cannot":[73],"perfectly":[75],"retrieved/output":[76],"as":[77,126,128],"QSTI":[79],"will":[80,232],"collapse":[81],"some":[83,134],"eigenstate":[84],"once":[85],"measured.":[88],"Owing":[89],"these":[91],"challenges,":[92],"current":[93],"technologies":[97],"only":[99],"achieve":[100],"classification-level":[101],"applications":[102],"requiring":[103],"a":[105,111,164,175],"few":[106,124],"output":[107],"qubits.":[108],"We":[109],"design":[110,221],"deep":[114,226],"network":[115],"(HyperQUEEN)":[116],"encode":[118],"information":[121],"qubits,":[125],"learn":[130],"mapping":[132],"from":[133],"measuring":[135],"statistics":[136],"(associated":[137],"with":[138,229],"collapsed-QSTI)":[140],"(instead":[145],"directly":[147],"retrieving":[148],"unobservable":[150],"QSTI),":[151],"thereby":[152],"solving":[153],"challenges.":[155],"HyperQUEEN":[156],"first":[159],"architecture":[161],"that":[162],"makes":[163],"breakthrough":[165],"blindly":[167],"reconstruct":[168],"NASA\u2019s":[169],"damaged":[170],"images,":[172],"which":[173],"means":[174],"lot":[176],"for":[177],"upcoming":[179],"space":[180],"era.":[181],"As":[182],"immature":[184],"facility":[186],"nowadays":[187],"does":[188],"not":[189,201],"yet":[190],"allow":[191],"us":[192],"fully":[194],"exhibit":[195],"high":[197],"potential,":[198],"we":[199],"are":[200,208],"aiming":[202],"at":[203],"developing":[204],"state-of-the-art":[205],"methods,":[206],"but":[207],"demonstrating":[209],"feasibility":[211],"sensing.":[216],"Mathematical":[217],"analysis":[218],"guiding":[219],"our":[220],"toward":[222],"low-rank":[224],"network,":[227],"together":[228],"comprehensive":[230],"experiments,":[231],"also":[233],"reported.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":8}],"updated_date":"2026-03-14T08:43:22.919905","created_date":"2025-10-10T00:00:00"}