{"id":"https://openalex.org/W4384341151","doi":"https://doi.org/10.3390/rs15143532","title":"A Deep Learning-Based Hyperspectral Object Classification Approach via Imbalanced Training Samples Handling","display_name":"A Deep Learning-Based Hyperspectral Object Classification Approach via Imbalanced Training Samples Handling","publication_year":2023,"publication_date":"2023-07-13","ids":{"openalex":"https://openalex.org/W4384341151","doi":"https://doi.org/10.3390/rs15143532"},"language":"en","primary_location":{"id":"doi:10.3390/rs15143532","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15143532","pdf_url":"https://www.mdpi.com/2072-4292/15/14/3532/pdf?version=1689257612","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/2072-4292/15/14/3532/pdf?version=1689257612","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058813589","display_name":"Md. Touhid Islam","orcid":"https://orcid.org/0009-0007-9437-8299"},"institutions":[{"id":"https://openalex.org/I197842652","display_name":"Hajee Mohammad Danesh Science and Technology University","ror":"https://ror.org/00kvxt616","country_code":"BD","type":"education","lineage":["https://openalex.org/I197842652"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Md Touhid Islam","raw_affiliation_strings":["Department of Computer Science and Engineering, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh","institution_ids":["https://openalex.org/I197842652"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032219102","display_name":"Md. Rashedul Islam","orcid":"https://orcid.org/0000-0003-3475-4217"},"institutions":[{"id":"https://openalex.org/I197842652","display_name":"Hajee Mohammad Danesh Science and Technology University","ror":"https://ror.org/00kvxt616","country_code":"BD","type":"education","lineage":["https://openalex.org/I197842652"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Md Rashedul Islam","raw_affiliation_strings":["Department of Computer Science and Engineering, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh","institution_ids":["https://openalex.org/I197842652"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000628690","display_name":"Md Palash Uddin","orcid":"https://orcid.org/0000-0002-4429-6590"},"institutions":[{"id":"https://openalex.org/I197842652","display_name":"Hajee Mohammad Danesh Science and Technology University","ror":"https://ror.org/00kvxt616","country_code":"BD","type":"education","lineage":["https://openalex.org/I197842652"]},{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU","BD"],"is_corresponding":false,"raw_author_name":"Md Palash Uddin","raw_affiliation_strings":["Department of Computer Science and Engineering, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh","School of Information Technology, Deakin University, Geelong, VIC 3220, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh","institution_ids":["https://openalex.org/I197842652"]},{"raw_affiliation_string":"School of Information Technology, Deakin University, Geelong, VIC 3220, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030762278","display_name":"Anwaar Ulhaq","orcid":"https://orcid.org/0000-0002-5145-7276"},"institutions":[{"id":"https://openalex.org/I153230381","display_name":"Charles Sturt University","ror":"https://ror.org/00wfvh315","country_code":"AU","type":"education","lineage":["https://openalex.org/I153230381"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Anwaar Ulhaq","raw_affiliation_strings":["School of Computing, Mathematics and Engineering, Charles Sturt University, Port Macquarie, NSW 2444, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing, Mathematics and Engineering, Charles Sturt University, Port Macquarie, NSW 2444, Australia","institution_ids":["https://openalex.org/I153230381"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5030762278"],"corresponding_institution_ids":["https://openalex.org/I153230381"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.9255,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.8764839,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"15","issue":"14","first_page":"3532","last_page":"3532"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9532999992370605,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9221000075340271,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8350880742073059},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7354581356048584},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7221586108207703},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7166380882263184},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6855630874633789},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.64971923828125},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5349646210670471},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48735862970352173},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.45938900113105774},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4215809106826782},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3610144853591919}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8350880742073059},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7354581356048584},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7221586108207703},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7166380882263184},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6855630874633789},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.64971923828125},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5349646210670471},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48735862970352173},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.45938900113105774},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4215809106826782},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3610144853591919},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/rs15143532","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15143532","pdf_url":"https://www.mdpi.com/2072-4292/15/14/3532/pdf?version=1689257612","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:pure.atira.dk:publications/53348af0-824e-4aa9-8f40-5fa78083a2fc","is_oa":true,"landing_page_url":"https://researchoutput.csu.edu.au/en/publications/53348af0-824e-4aa9-8f40-5fa78083a2fc","pdf_url":null,"source":{"id":"https://openalex.org/S7407055442","display_name":"Charles Sturt University Research Output (CRO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Islam, M T, Islam, M R, Uddin, M P & Ulhaq, A 2023, 'A deep learning-based hyperspectral object classification approach via imbalanced training samples handling', Remote Sensing, vol. 15, no. 14, 3532, pp. 1-29. https://doi.org/10.3390/rs15143532","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:doaj.org/article:0d25ef41adba4b14b9a15e1635bc1958","is_oa":true,"landing_page_url":"https://doaj.org/article/0d25ef41adba4b14b9a15e1635bc1958","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 15, Iss 14, p 3532 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/14/3532/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15143532","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 15; Issue 14; Pages: 3532","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15143532","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15143532","pdf_url":"https://www.mdpi.com/2072-4292/15/14/3532/pdf?version=1689257612","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":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384341151.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W121888192","https://openalex.org/W169052826","https://openalex.org/W1876219421","https://openalex.org/W1964325474","https://openalex.org/W1976381494","https://openalex.org/W1979713463","https://openalex.org/W2000895242","https://openalex.org/W2015452969","https://openalex.org/W2062821772","https://openalex.org/W2121076756","https://openalex.org/W2121338139","https://openalex.org/W2148143831","https://openalex.org/W2152174305","https://openalex.org/W2157621128","https://openalex.org/W2324167749","https://openalex.org/W2341545927","https://openalex.org/W2521504039","https://openalex.org/W2572303978","https://openalex.org/W2573524522","https://openalex.org/W2742991909","https://openalex.org/W2894337953","https://openalex.org/W2902972690","https://openalex.org/W2906463556","https://openalex.org/W2914331134","https://openalex.org/W2993620107","https://openalex.org/W3011149747","https://openalex.org/W3011424859","https://openalex.org/W3014740345","https://openalex.org/W3022592629","https://openalex.org/W3035707407","https://openalex.org/W3040978759","https://openalex.org/W3048506115","https://openalex.org/W3081910372","https://openalex.org/W3116252251","https://openalex.org/W3130265010","https://openalex.org/W3214916067","https://openalex.org/W4253605667","https://openalex.org/W4285172160","https://openalex.org/W4290044412","https://openalex.org/W4293198074","https://openalex.org/W6606879723","https://openalex.org/W6704443453","https://openalex.org/W6727156235","https://openalex.org/W6774677333","https://openalex.org/W6781936015","https://openalex.org/W6842032011"],"related_works":["https://openalex.org/W2132083814","https://openalex.org/W2292979300","https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081"],"abstract_inverted_index":{"Object":[0],"classification":[1,29,116,164],"in":[2,130,200],"hyperspectral":[3,19,155,201],"images":[4],"involves":[5],"accurately":[6],"categorizing":[7],"objects":[8],"based":[9],"on":[10,144,178],"their":[11],"spectral":[12],"characteristics.":[13],"However,":[14],"the":[15,66,74,125,131,145,179,192],"high":[16,195],"dimensionality":[17,41,59,196],"of":[18,133,173,194],"data":[20,75,89],"and":[21,43,64,87,104,113,135,150,176,197],"class":[22,80,198],"imbalance":[23,199],"pose":[24],"significant":[25],"challenges":[26,193],"to":[27,62,78,109,159,190],"object":[28,163,202],"performance.":[30],"To":[31],"address":[32],"these":[33],"challenges,":[34],"we":[35,123],"propose":[36],"a":[37,49,56,94,100,105,187],"framework":[38,54],"that":[39],"incorporates":[40],"reduction":[42,60],"re-sampling":[44],"as":[45],"preprocessing":[46],"steps":[47],"for":[48],"deep":[50],"learning":[51,102,107],"model.":[52],"Our":[53,162],"employs":[55],"novel":[57],"subgroup-based":[58],"technique":[61,165],"extract":[63,110],"select":[65],"most":[67],"informative":[68],"features":[69,112],"with":[70,170],"minimal":[71],"redundancy.":[72],"Additionally,":[73],"are":[76,90],"resampled":[77],"achieve":[79,114],"balance":[81],"across":[82],"all":[83],"categories.":[84],"The":[85],"reduced":[86],"balanced":[88],"then":[91],"processed":[92],"through":[93],"hybrid":[95,121],"CNN":[96],"model,":[97],"which":[98],"combines":[99],"3D":[101],"block":[103,108],"2D":[106],"spectral\u2013spatial":[111],"satisfactory":[115],"accuracy.":[117],"By":[118],"adopting":[119],"this":[120],"approach,":[122],"simplify":[124],"model":[126,143],"while":[127],"improving":[128],"performance":[129],"presence":[132],"noise":[134],"limited":[136],"sample":[137],"size.":[138],"We":[139],"evaluated":[140],"our":[141],"proposed":[142,184],"Salinas":[146],"scene,":[147],"Pavia":[148],"University,":[149],"Kennedy":[151],"Space":[152],"Center":[153],"benchmark":[154],"datasets,":[156,181],"comparing":[157],"it":[158],"state-of-the-art":[160],"methods.":[161],"achieves":[166],"highly":[167],"promising":[168],"results,":[169],"overall":[171],"accuracies":[172],"99.98%,":[174],"99.94%,":[175],"99.46%":[177],"three":[180],"respectively.":[182],"This":[183],"approach":[185],"offers":[186],"compelling":[188],"solution":[189],"overcome":[191],"classification.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2023-07-15T00:00:00"}