{"id":"https://openalex.org/W4313044690","doi":"https://doi.org/10.1109/whispers56178.2022.9955106","title":"Deep Self-Supervised Pixel-Level Learning For Hyperspectral Classification","display_name":"Deep Self-Supervised Pixel-Level Learning For Hyperspectral Classification","publication_year":2022,"publication_date":"2022-09-13","ids":{"openalex":"https://openalex.org/W4313044690","doi":"https://doi.org/10.1109/whispers56178.2022.9955106"},"language":"en","primary_location":{"id":"doi:10.1109/whispers56178.2022.9955106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers56178.2022.9955106","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-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/A5022930273","display_name":"Jonathan Gonz\u00e1lez-Santiago","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jonathan Gonzalez-Santiago","raw_affiliation_strings":["Fraunhofer IOSB, Gutleuthausstr. 1,Ettlingen,Germany,76275"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IOSB, Gutleuthausstr. 1,Ettlingen,Germany,76275","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002890036","display_name":"Fabian Schenkel","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Schenkel","raw_affiliation_strings":["Fraunhofer IOSB, Gutleuthausstr. 1,Ettlingen,Germany,76275"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IOSB, Gutleuthausstr. 1,Ettlingen,Germany,76275","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031865300","display_name":"Wolfgang Gro\u00df","orcid":"https://orcid.org/0000-0002-8430-0734"},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfgang Gross","raw_affiliation_strings":["Fraunhofer IOSB, Gutleuthausstr. 1,Ettlingen,Germany,76275"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IOSB, Gutleuthausstr. 1,Ettlingen,Germany,76275","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075370224","display_name":"Wolfgang Middelmann","orcid":"https://orcid.org/0000-0002-3507-7396"},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfgang Middelmann","raw_affiliation_strings":["Fraunhofer IOSB, Gutleuthausstr. 1,Ettlingen,Germany,76275"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IOSB, Gutleuthausstr. 1,Ettlingen,Germany,76275","institution_ids":["https://openalex.org/I4210111500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5022930273"],"corresponding_institution_ids":["https://openalex.org/I4210111500"],"apc_list":null,"apc_paid":null,"fwci":0.22,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57321003,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9789000153541565,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.977400004863739,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8031520843505859},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7896285653114319},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7492834329605103},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7094250917434692},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6674478650093079},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6444047689437866},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5697560906410217},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5260279774665833},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5213631391525269},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4702911376953125},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46566084027290344},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46042749285697937},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4532420039176941},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4293852150440216},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4214911460876465},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4121052026748657},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2342076599597931}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8031520843505859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7896285653114319},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7492834329605103},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7094250917434692},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6674478650093079},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6444047689437866},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5697560906410217},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5260279774665833},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5213631391525269},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4702911376953125},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46566084027290344},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46042749285697937},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4532420039176941},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4293852150440216},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4214911460876465},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4121052026748657},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2342076599597931},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/whispers56178.2022.9955106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers56178.2022.9955106","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"},{"id":"pmh:oai:null:publica/429208","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/429208","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2053154970","https://openalex.org/W2108598243","https://openalex.org/W2114819256","https://openalex.org/W2194775991","https://openalex.org/W2931204392","https://openalex.org/W2987283559","https://openalex.org/W3035524453","https://openalex.org/W3172615411","https://openalex.org/W3206737592","https://openalex.org/W4206307542"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2060875994","https://openalex.org/W2027399350","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2515319207"],"abstract_inverted_index":{"The":[0,89],"task":[1,124],"of":[2,49,100,105,141,147],"hyperspectral":[3,84],"classification":[4,137,157],"plays":[5],"an":[6,50],"important":[7],"role":[8],"in":[9],"decision-making":[10],"processes.":[11],"It":[12],"is":[13],"mainly":[14],"solved":[15],"applying":[16],"supervised":[17],"deep":[18],"learning":[19,32,73],"techniques":[20,45],"that":[21,98,151],"require":[22],"numerous":[23],"well-annotated":[24],"pixels.":[25],"Recently":[26],"developed":[27],"methods":[28],"based":[29],"on":[30,38,165],"contrastive":[31,72],"attempt":[33],"to":[34,77,110,118,134],"alleviate":[35],"this":[36,66],"dependency":[37],"abundant":[39],"labels.":[40,88,142],"To":[41,64],"learn":[42,78],"representations,":[43],"these":[44],"distinguish":[46],"between":[47],"views":[48,104],"image":[51,108],"patch,":[52],"which":[53],"could":[54],"be":[55],"unfavorable":[56],"for":[57,82,125],"downstream":[58],"tasks":[59],"requiring":[60],"dense":[61],"pixel":[62,122],"predictions.":[63],"overcome":[65],"challenge,":[67],"the":[68,75,93,106,121,129,136,148,152],"current":[69],"work":[70],"exploits":[71],"at":[74],"pixel-level":[76],"robust":[79],"feature":[80,112,126],"representations":[81,131],"classifying":[83],"imagery":[85],"with":[86,92,144],"fewer":[87],"method":[90,154],"starts":[91],"Self-Supervised":[94],"Learning":[95],"(SSL)":[96],"phase":[97],"consists":[99],"sampling":[101],"two":[102],"augmented":[103],"same":[107],"patch":[109],"compute":[111],"maps.":[113],"These":[114],"are":[115,132],"subsequently":[116],"used":[117],"carry":[119],"out":[120],"discrimination":[123],"learning.":[127],"Afterwards,":[128],"learned":[130],"transferred":[133],"solve":[135],"using":[138],"different":[139],"amounts":[140],"Experiments":[143],"only":[145],"one-tenth":[146],"labels":[149],"show":[150],"proposed":[153],"achieves":[155],"better":[156],"results":[158],"than":[159],"well-established":[160],"methods,":[161],"including":[162],"those":[163],"trained":[164],"Image-Net.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}