{"id":"https://openalex.org/W2011572176","doi":"https://doi.org/10.1109/igarss.2015.7326064","title":"Nonlinear endmember extraction in earth observations and astroinformatics data interpretation and compression","display_name":"Nonlinear endmember extraction in earth observations and astroinformatics data interpretation and compression","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W2011572176","doi":"https://doi.org/10.1109/igarss.2015.7326064","mag":"2011572176"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2015.7326064","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7326064","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","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/A5083495404","display_name":"Andrea Marinoni","orcid":"https://orcid.org/0000-0001-6789-0915"},"institutions":[{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Andrea Marinoni","raw_affiliation_strings":["Dip. di Ingegneria Industriale e dell'lnformazione, Universita degli Studi di Pavia, Pavia, Italy","Dip. di Ingegneria Industriale e dell'Informazione, Universit\u00e0 degli Studi di Pavia, Pavia, Italy. Via Ferrata 5, I-27100, Pavia, Italy"],"affiliations":[{"raw_affiliation_string":"Dip. di Ingegneria Industriale e dell'lnformazione, Universita degli Studi di Pavia, Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]},{"raw_affiliation_string":"Dip. di Ingegneria Industriale e dell'Informazione, Universit\u00e0 degli Studi di Pavia, Pavia, Italy. Via Ferrata 5, I-27100, Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006623289","display_name":"Paolo Gamba","orcid":"https://orcid.org/0000-0002-9576-6337"},"institutions":[{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Gamba","raw_affiliation_strings":["Dip. di Ingegneria Industriale e dell'lnformazione, Universita degli Studi di Pavia, Pavia, Italy","Dip. di Ingegneria Industriale e dell'Informazione, Universit\u00e0 degli Studi di Pavia, Pavia, Italy. Via Ferrata 5, I-27100, Pavia, Italy"],"affiliations":[{"raw_affiliation_string":"Dip. di Ingegneria Industriale e dell'lnformazione, Universita degli Studi di Pavia, Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]},{"raw_affiliation_string":"Dip. di Ingegneria Industriale e dell'Informazione, Universit\u00e0 degli Studi di Pavia, Pavia, Italy. Via Ferrata 5, I-27100, Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083495404"],"corresponding_institution_ids":["https://openalex.org/I25217355"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.0658999,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1500","last_page":"1503"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9926000237464905,"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"}},"topics":[{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9926000237464905,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9890000224113464,"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":0.9776999950408936,"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/lossless-compression","display_name":"Lossless compression","score":0.7192058563232422},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6772903800010681},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.6246008276939392},{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.5410870313644409},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.5097982287406921},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.49554669857025146},{"id":"https://openalex.org/keywords/simplex","display_name":"Simplex","score":0.45671573281288147},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.436953067779541},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4223015010356903},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3990921378135681},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.358095645904541},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2819202244281769},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1561601758003235},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15106508135795593},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.13271090388298035}],"concepts":[{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.7192058563232422},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6772903800010681},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.6246008276939392},{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.5410870313644409},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.5097982287406921},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.49554669857025146},{"id":"https://openalex.org/C62438384","wikidata":"https://www.wikidata.org/wiki/Q331350","display_name":"Simplex","level":2,"score":0.45671573281288147},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.436953067779541},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4223015010356903},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3990921378135681},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.358095645904541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2819202244281769},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1561601758003235},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15106508135795593},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.13271090388298035},{"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2015.7326064","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7326064","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","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":13,"referenced_works":["https://openalex.org/W1963659868","https://openalex.org/W1965914555","https://openalex.org/W1991480333","https://openalex.org/W2023791222","https://openalex.org/W2125245676","https://openalex.org/W2163886442","https://openalex.org/W2167035035","https://openalex.org/W2765961813","https://openalex.org/W2766051188","https://openalex.org/W2767012171","https://openalex.org/W6678451760","https://openalex.org/W6746120394","https://openalex.org/W6746153962"],"related_works":["https://openalex.org/W2609138370","https://openalex.org/W2416971058","https://openalex.org/W2117544941","https://openalex.org/W2119886624","https://openalex.org/W2139141917","https://openalex.org/W2113095280","https://openalex.org/W2948148442","https://openalex.org/W2461250372","https://openalex.org/W2394342941","https://openalex.org/W2169853506"],"abstract_inverted_index":{"As":[0],"remotely":[1],"sensed":[2],"Big":[3],"Data":[4],"applications":[5],"in":[6,12,79],"astrophysics":[7],"research":[8],"have":[9],"been":[10],"flourishing":[11],"the":[13,16,59,68,84,97,101,116,120,128],"last":[14],"decade,":[15],"need":[17],"for":[18,26,45,137],"a":[19,42,72,76,80,93],"new":[20,60],"class":[21],"of":[22,33,48,67,96,100],"techniques":[23],"and":[24,31,141],"methods":[25],"efficient":[27,106],"storage,":[28],"compression,":[29],"retrieval":[30],"investigation":[32],"astronomical":[34],"datasets":[35,50],"has":[36],"become":[37],"urgent.":[38],"In":[39],"this":[40],"paper,":[41],"novel":[43],"strategy":[44],"lossless":[46],"compression":[47,107,135],"large":[49],"composed":[51],"by":[52,111,115],"remote":[53],"sensing":[54],"records":[55],"is":[56],"introduced.":[57],"Specifically,":[58],"approach":[61],"aims":[62,87],"at":[63,88],"describing":[64,112],"each":[65],"sample":[66,91],"given":[69],"dataset":[70],"as":[71,92],"point":[73],"living":[74],"within":[75],"convex":[77],"hull":[78],"multidimensional":[81,103],"space.":[82],"Thus,":[83],"proposed":[85,129],"framework":[86],"characterizing":[89],"every":[90],"nonlinear":[94,121],"combination":[95],"extremal":[98],"points":[99],"aforesaid":[102],"simplex.":[104],"Therefore,":[105],"can":[108,131],"be":[109],"achieved":[110],"those":[113],"samples":[114],"parameters":[117],"that":[118],"drive":[119],"mixture":[122],"only.":[123],"Experimental":[124],"results":[125],"show":[126],"how":[127],"architecture":[130],"effectively":[132],"deliver":[133],"great":[134],"performance":[136],"both":[138],"Earth":[139],"observations":[140],"planetary":[142],"records.":[143]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}