{"id":"https://openalex.org/W3164802645","doi":"https://doi.org/10.3390/rs13091732","title":"Distance Transform-Based Spectral-Spatial Feature Vector for Hyperspectral Image Classification with Stacked Autoencoder","display_name":"Distance Transform-Based Spectral-Spatial Feature Vector for Hyperspectral Image Classification with Stacked Autoencoder","publication_year":2021,"publication_date":"2021-04-29","ids":{"openalex":"https://openalex.org/W3164802645","doi":"https://doi.org/10.3390/rs13091732","mag":"3164802645"},"language":"en","primary_location":{"id":"doi:10.3390/rs13091732","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13091732","pdf_url":"https://www.mdpi.com/2072-4292/13/9/1732/pdf?version=1619792159","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/2072-4292/13/9/1732/pdf?version=1619792159","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068414496","display_name":"Hadis Madani","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Hadis Madani","raw_affiliation_strings":["Electrical and Computer Engineering Department, Western University, London, ON N6A 3K7, Canada"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Western University, London, ON N6A 3K7, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109815499","display_name":"Kenneth McIsaac","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Kenneth McIsaac","raw_affiliation_strings":["Electrical and Computer Engineering Department, Western University, London, ON N6A 3K7, Canada"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Western University, London, ON N6A 3K7, Canada","institution_ids":["https://openalex.org/I125749732"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5068414496"],"corresponding_institution_ids":["https://openalex.org/I125749732"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.0108,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.78975181,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"13","issue":"9","first_page":"1732","last_page":"1732"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9941999912261963,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9478999972343445,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.857129693031311},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7827959656715393},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7269370555877686},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7007920145988464},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6638711094856262},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5888027548789978},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5505098700523376},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5429252982139587},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4968307316303253},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4757772982120514},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.34326714277267456},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.30586493015289307},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15443778038024902}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.857129693031311},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7827959656715393},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7269370555877686},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7007920145988464},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6638711094856262},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5888027548789978},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5505098700523376},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5429252982139587},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4968307316303253},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4757772982120514},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.34326714277267456},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30586493015289307},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15443778038024902},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs13091732","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13091732","pdf_url":"https://www.mdpi.com/2072-4292/13/9/1732/pdf?version=1619792159","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:c53cf70a106b4a70904831fd4f612d46","is_oa":true,"landing_page_url":"https://doaj.org/article/c53cf70a106b4a70904831fd4f612d46","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 13, Iss 9, p 1732 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/13/9/1732/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs13091732","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; Volume 13; Issue 9; Pages: 1732","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs13091732","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13091732","pdf_url":"https://www.mdpi.com/2072-4292/13/9/1732/pdf?version=1619792159","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":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3164802645.pdf","grobid_xml":"https://content.openalex.org/works/W3164802645.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W2029316659","https://openalex.org/W2059217921","https://openalex.org/W2079922832","https://openalex.org/W2083541351","https://openalex.org/W2090424610","https://openalex.org/W2105464873","https://openalex.org/W2127199143","https://openalex.org/W2131864940","https://openalex.org/W2134560790","https://openalex.org/W2136251662","https://openalex.org/W2170946361","https://openalex.org/W2171171329","https://openalex.org/W2291011663","https://openalex.org/W2345128667","https://openalex.org/W2548791488","https://openalex.org/W2550305603","https://openalex.org/W2560523472","https://openalex.org/W2587790406","https://openalex.org/W2765596918","https://openalex.org/W2793846146","https://openalex.org/W2794633256","https://openalex.org/W2799338146","https://openalex.org/W2803948506","https://openalex.org/W2898237049","https://openalex.org/W2963727962","https://openalex.org/W6684897833"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2072166414","https://openalex.org/W2752972570","https://openalex.org/W4297051394","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W2734887215"],"abstract_inverted_index":{"Pixel-wise":[0],"classification":[1,66,85],"of":[2,42,55,122,142,147,154,198],"hyperspectral":[3,189],"images":[4],"(HSIs)":[5],"from":[6,211],"remote":[7],"sensing":[8],"data":[9],"is":[10,68,116],"a":[11,40,48,53,61,101],"common":[12],"approach":[13],"for":[14],"extracting":[15],"information":[16,75],"about":[17],"scenes.":[18],"In":[19,96,135,191],"recent":[20],"years,":[21],"approaches":[22],"based":[23,117],"on":[24,118],"deep":[25,232],"learning":[26],"techniques":[27],"have":[28,184],"gained":[29],"wide":[30],"applicability.":[31],"An":[32],"HSI":[33,206],"dataset":[34,149],"can":[35],"be":[36],"viewed":[37],"either":[38],"as":[39,52,225,227],"collection":[41,54],"images,":[43],"each":[44,57,155],"one":[45,58],"captured":[46],"at":[47],"different":[49],"wavelength,":[50],"or":[51],"spectra,":[56],"associated":[59],"with":[60,125,187],"specific":[62],"point":[63],"(pixel).":[64],"Enhanced":[65],"accuracy":[67],"enabled":[69],"if":[70],"the":[71,79,119,123,128,132,140,148,152,158,165,178,194],"spectral":[72,88],"and":[73,196],"spatial":[74,103,159,180],"are":[76,202],"combined":[77],"in":[78,109,131,205],"input":[80,133],"vector.":[81,161,182],"This":[82],"allows":[83],"simultaneous":[84],"according":[86,92],"to":[87,93,127,150,157,172,177,193,222,228],"type":[89],"but":[90],"also":[91],"geometric":[94,145,175],"relationships.":[95],"this":[97],"study,":[98],"we":[99,138,163,208],"proposed":[100,113,179,217],"novel":[102],"feature":[104,114,160,181],"vector":[105,115],"which":[106,201],"improves":[107],"accuracies":[108],"pixel-wise":[110],"classification.":[111],"Our":[112,216],"distance":[120],"transform":[121],"pixels":[124,143],"respect":[126],"dominant":[129],"edges":[130],"HSI.":[134],"other":[136],"words,":[137],"allow":[139],"location":[141],"within":[144],"subdivisions":[146],"modify":[151],"contribution":[153],"pixel":[156],"Moreover,":[162],"used":[164,204],"extended":[166],"multi":[167],"attribute":[168],"profile":[169],"(EMAP)":[170],"features":[171,176],"add":[173],"more":[174],"We":[183],"performed":[185],"experiments":[186],"three":[188],"datasets.":[190],"addition":[192],"Salinas":[195],"University":[197],"Pavia":[199],"datasets,":[200],"commonly":[203],"research,":[207],"include":[209],"samples":[210],"our":[212],"Surrey":[213],"BC":[214],"dataset.":[215],"method":[218],"results":[219],"compares":[220],"favorably":[221],"traditional":[223],"algorithms":[224],"well":[226],"some":[229],"recently":[230],"published":[231],"learning-based":[233],"algorithms.":[234]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2021-06-07T00:00:00"}
