{"id":"https://openalex.org/W4290755749","doi":"https://doi.org/10.3390/rs14153766","title":"Learned Design of a Compressive Hyperspectral Imager for Remote Sensing by a Physics-Constrained Autoencoder","display_name":"Learned Design of a Compressive Hyperspectral Imager for Remote Sensing by a Physics-Constrained Autoencoder","publication_year":2022,"publication_date":"2022-08-05","ids":{"openalex":"https://openalex.org/W4290755749","doi":"https://doi.org/10.3390/rs14153766"},"language":"en","primary_location":{"id":"doi:10.3390/rs14153766","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14153766","pdf_url":"https://www.mdpi.com/2072-4292/14/15/3766/pdf?version=1659708788","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/15/3766/pdf?version=1659708788","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050182357","display_name":"Yaron Heiser","orcid":null},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Yaron Heiser","raw_affiliation_strings":["Electro-Optics and Photonics Department, School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer Sheva 8410501, Israel"],"affiliations":[{"raw_affiliation_string":"Electro-Optics and Photonics Department, School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer Sheva 8410501, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004500738","display_name":"Adrian Stern","orcid":"https://orcid.org/0000-0002-3696-7526"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Adrian Stern","raw_affiliation_strings":["Electro-Optics and Photonics Department, School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer Sheva 8410501, Israel"],"affiliations":[{"raw_affiliation_string":"Electro-Optics and Photonics Department, School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer Sheva 8410501, Israel","institution_ids":["https://openalex.org/I124227911"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5050182357"],"corresponding_institution_ids":["https://openalex.org/I124227911"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.9967,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.69870705,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"14","issue":"15","first_page":"3766","last_page":"3766"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.9991999864578247,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/autoencoder","display_name":"Autoencoder","score":0.8833922147750854},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8241984248161316},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6372463703155518},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5365614295005798},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5333355069160461},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5264666676521301},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5230187773704529},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.49279525876045227},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4615288972854614},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35852017998695374},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1399141252040863}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8833922147750854},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8241984248161316},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6372463703155518},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5365614295005798},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5333355069160461},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5264666676521301},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5230187773704529},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.49279525876045227},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4615288972854614},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35852017998695374},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1399141252040863},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14153766","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14153766","pdf_url":"https://www.mdpi.com/2072-4292/14/15/3766/pdf?version=1659708788","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:83f6efe3ea0f44bfbebe7c2dbf327a15","is_oa":true,"landing_page_url":"https://doaj.org/article/83f6efe3ea0f44bfbebe7c2dbf327a15","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 15, p 3766 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/15/3766/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14153766","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14153766","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14153766","pdf_url":"https://www.mdpi.com/2072-4292/14/15/3766/pdf?version=1659708788","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5699999928474426}],"awards":[{"id":"https://openalex.org/G5134728399","display_name":null,"funder_award_id":"3-13351","funder_id":"https://openalex.org/F4320320948","funder_display_name":"Ministry of Science, Technology and Space"},{"id":"https://openalex.org/G551639140","display_name":null,"funder_award_id":"3-18410","funder_id":"https://openalex.org/F4320320948","funder_display_name":"Ministry of Science, Technology and Space"}],"funders":[{"id":"https://openalex.org/F4320320948","display_name":"Ministry of Science, Technology and Space","ror":"https://ror.org/02heb2n75"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4290755749.pdf","grobid_xml":"https://content.openalex.org/works/W4290755749.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1600877088","https://openalex.org/W1966544095","https://openalex.org/W1973973473","https://openalex.org/W2000019232","https://openalex.org/W2003032218","https://openalex.org/W2010265430","https://openalex.org/W2025483702","https://openalex.org/W2042978621","https://openalex.org/W2079407536","https://openalex.org/W2093888557","https://openalex.org/W2112531993","https://openalex.org/W2116720609","https://openalex.org/W2116955354","https://openalex.org/W2133665775","https://openalex.org/W2138621882","https://openalex.org/W2192817454","https://openalex.org/W2312472563","https://openalex.org/W2317670484","https://openalex.org/W2564048308","https://openalex.org/W2590877996","https://openalex.org/W2604003557","https://openalex.org/W2616474338","https://openalex.org/W2782517596","https://openalex.org/W2895922150","https://openalex.org/W2906076216","https://openalex.org/W2928182459","https://openalex.org/W2928260953","https://openalex.org/W2945274755","https://openalex.org/W2991265376","https://openalex.org/W3008838958","https://openalex.org/W3013529009","https://openalex.org/W3049737467","https://openalex.org/W3091771023","https://openalex.org/W3100011500","https://openalex.org/W3138725786","https://openalex.org/W3142104381","https://openalex.org/W3171952126","https://openalex.org/W4221090720","https://openalex.org/W4235838711","https://openalex.org/W4237583811","https://openalex.org/W4248150465","https://openalex.org/W4253218940","https://openalex.org/W4300420063","https://openalex.org/W4388375774","https://openalex.org/W6677463967","https://openalex.org/W6747966163","https://openalex.org/W6782191381","https://openalex.org/W6785314854"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W2072166414","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W3209970181","https://openalex.org/W2076134148"],"abstract_inverted_index":{"Designing":[0],"and":[1,23,80],"optimizing":[2],"systems":[3],"by":[4,144,165],"end-to-end":[5],"deep":[6,66],"learning":[7,67],"is":[8,138],"a":[9,15,26,32,37,74,81,90,103,109,114,145],"recently":[10],"emerging":[11],"field.":[12],"We":[13,63],"present":[14],"novel":[16],"physics-constrained":[17],"autoencoder":[18,143],"(PyCAE)":[19],"for":[20,42],"the":[21,123,158,173,177,183,186],"design":[22,36,70],"optimization":[24],"of":[25,53,89,92,113,176,182],"physically":[27,168],"realizable":[28,169],"sensing":[29,44,152,170],"model.":[30],"As":[31],"case":[33],"study,":[34],"we":[35],"compressive":[38],"hyperspectral":[39],"imaging":[40],"system":[41],"remote":[43,151],"based":[45],"on":[46],"this":[47],"approach,":[48,147],"which":[49],"allows":[50],"capturing":[51],"hundreds":[52],"spectral":[54,71,75,116,187],"bands":[55],"with":[56,73,141],"as":[57,59],"few":[58,110],"four":[60],"compressed":[61],"measurements.":[62],"demonstrate":[64],"our":[65],"approach":[68],"to":[69,101,156],"compression":[72],"light":[76],"modulator":[77],"(SpLM)":[78],"encoder":[79,174],"reconstruction":[82],"neural":[83],"network":[84],"decoder.":[85],"The":[86,118,136,160,179],"SpLM":[87,137],"consists":[88],"set":[91],"modified":[93],"Fabry\u2013P\u00e9rot":[94],"resonator":[95],"(mFPR)":[96],"etalons":[97],"that":[98],"are":[99,154,163],"designed":[100,140],"have":[102],"staircase-shaped":[104],"geometry.":[105],"Each":[106],"stair":[107],"occupies":[108],"pixel":[111],"columns":[112],"push-broom-like":[115],"imager.":[117],"mFPR\u2019s":[119],"stairs":[120],"can":[121],"sample":[122],"earth":[124],"terrain":[125],"in":[126,172],"along-track":[127],"scanning":[128],"from":[129,150],"an":[130,142],"airborne":[131],"or":[132],"spaceborne":[133],"moving":[134],"platform.":[135],"jointly":[139],"data-driven":[146],"while":[148],"spectra":[149],"databases":[153],"used":[155],"train":[157],"system.":[159],"SpLM\u2019s":[161],"parameters":[162],"optimized":[164],"integrating":[166],"its":[167],"model":[171],"part":[175,181],"PyCAE.":[178],"decoder":[180],"PyCAE":[184],"implements":[185],"reconstruction.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}