{"id":"https://openalex.org/W3167109952","doi":"https://doi.org/10.1109/jstars.2021.3088228","title":"Morphological Convolutional Neural Networks for Hyperspectral Image Classification","display_name":"Morphological Convolutional Neural Networks for Hyperspectral Image Classification","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3167109952","doi":"https://doi.org/10.1109/jstars.2021.3088228","mag":"3167109952"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2021.3088228","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2021.3088228","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9314330/09451651.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/9314330/09451651.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087427076","display_name":"Swalpa Kumar Roy","orcid":"https://orcid.org/0000-0002-6580-3977"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Swalpa Roy","raw_affiliation_strings":["Department of Computer Science and Engineering, Jalpaiguri Government Engineering College, Jalpaiguri, India","ORCiD"],"raw_orcid":"https://orcid.org/0000-0002-6580-3977","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Jalpaiguri Government Engineering College, Jalpaiguri, India","institution_ids":[]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074408392","display_name":"Ranjan Mondal","orcid":null},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ranjan Mondal","raw_affiliation_strings":["Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046123228","display_name":"Mercedes E. Paoletti","orcid":"https://orcid.org/0000-0003-1030-3729"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Mercedes E. Paoletti","raw_affiliation_strings":["Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","ORCiD","Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C&#x00E1;ceres, Spain"],"raw_orcid":"https://orcid.org/0000-0003-1030-3729","affiliations":[{"raw_affiliation_string":"Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]},{"raw_affiliation_string":"Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C&#x00E1;ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039673511","display_name":"Juan M. Haut","orcid":"https://orcid.org/0000-0001-6701-961X"},"institutions":[{"id":"https://openalex.org/I178450904","display_name":"Universidad Nacional de Educaci\u00f3n a Distancia","ror":"https://ror.org/02msb5n36","country_code":"ES","type":"education","lineage":["https://openalex.org/I178450904"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan M. Haut","raw_affiliation_strings":["Department of Communication and Control Systems, Higher School of Computer Engineering, National Distance Education University, Madrid, Spain","ORCiD"],"raw_orcid":"https://orcid.org/0000-0001-6701-961X","affiliations":[{"raw_affiliation_string":"Department of Communication and Control Systems, Higher School of Computer Engineering, National Distance Education University, Madrid, Spain","institution_ids":["https://openalex.org/I178450904"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054292278","display_name":"Antonio Plaza","orcid":"https://orcid.org/0000-0002-9613-1659"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio Plaza","raw_affiliation_strings":["Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","ORCiD","Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C&#x00E1;ceres, Spain"],"raw_orcid":"https://orcid.org/0000-0002-9613-1659","affiliations":[{"raw_affiliation_string":"Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]},{"raw_affiliation_string":"Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C&#x00E1;ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":6.6698,"has_fulltext":true,"cited_by_count":101,"citation_normalized_percentile":{"value":0.97330118,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"14","issue":null,"first_page":"8689","last_page":"8702"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9958999752998352,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9836999773979187,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8315474987030029},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7005912065505981},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.698229193687439},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6097449660301208},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5796144008636475},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5737574696540833},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.39500153064727783},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33812215924263}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8315474987030029},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7005912065505981},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.698229193687439},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6097449660301208},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5796144008636475},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5737574696540833},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39500153064727783},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33812215924263}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2021.3088228","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2021.3088228","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9314330/09451651.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1640b4d90e424de2ac040c0f120e2c68","is_oa":true,"landing_page_url":"https://doaj.org/article/1640b4d90e424de2ac040c0f120e2c68","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 8689-8702 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2021.3088228","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2021.3088228","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9314330/09451651.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1058977399","display_name":null,"funder_award_id":"PID2019-110315RB-I00","funder_id":"https://openalex.org/F4320322930","funder_display_name":"Ministerio de Ciencia e Innovaci\u00f3n"},{"id":"https://openalex.org/G1731382246","display_name":null,"funder_award_id":"GR18060","funder_id":"https://openalex.org/F4320328352","funder_display_name":"Junta de Extremadura"},{"id":"https://openalex.org/G3690828678","display_name":null,"funder_award_id":"PID2019","funder_id":"https://openalex.org/F4320322930","funder_display_name":"Ministerio de Ciencia e Innovaci\u00f3n"},{"id":"https://openalex.org/G574691940","display_name":"TOOLS FOR MAPPING HUMAN EXPOSURE TO RISKY ENVIRONMENTAL CONDITIONS BY MEANS OF GROUND AND EARTH OBSERVATION DATA","funder_award_id":"734541","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G699448585","display_name":null,"funder_award_id":"734541","funder_id":"https://openalex.org/F4320328352","funder_display_name":"Junta de Extremadura"}],"funders":[{"id":"https://openalex.org/F4320316680","display_name":"University of Engineering and Technology, Lahore","ror":"https://ror.org/0051w2v06"},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320321837","display_name":"Ministerio de Econom\u00eda y Competitividad","ror":"https://ror.org/034900433"},{"id":"https://openalex.org/F4320322930","display_name":"Ministerio de Ciencia e Innovaci\u00f3n","ror":"https://ror.org/034900433"},{"id":"https://openalex.org/F4320328352","display_name":"Junta de Extremadura","ror":"https://ror.org/01df4mv68"},{"id":"https://openalex.org/F4320329409","display_name":"Rajshahi University","ror":"https://ror.org/05nnyr510"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1522301498","https://openalex.org/W1529220857","https://openalex.org/W1561442812","https://openalex.org/W1677182931","https://openalex.org/W1966580635","https://openalex.org/W2022470997","https://openalex.org/W2067532478","https://openalex.org/W2090424610","https://openalex.org/W2114819256","https://openalex.org/W2114828048","https://openalex.org/W2127199143","https://openalex.org/W2132934990","https://openalex.org/W2136251662","https://openalex.org/W2159070926","https://openalex.org/W2163994077","https://openalex.org/W2314785379","https://openalex.org/W2412588858","https://openalex.org/W2548776929","https://openalex.org/W2764276316","https://openalex.org/W2772452219","https://openalex.org/W2808098982","https://openalex.org/W2886468927","https://openalex.org/W2907920413","https://openalex.org/W2911437338","https://openalex.org/W2914331134","https://openalex.org/W2940678725","https://openalex.org/W2942454403","https://openalex.org/W2948981911","https://openalex.org/W2964121744","https://openalex.org/W2964199361","https://openalex.org/W2966205048","https://openalex.org/W2991616716","https://openalex.org/W2993134750","https://openalex.org/W3001283548","https://openalex.org/W3004877455","https://openalex.org/W3025719176","https://openalex.org/W3043248362","https://openalex.org/W3089160504","https://openalex.org/W3100011500","https://openalex.org/W3105357426","https://openalex.org/W3114720220","https://openalex.org/W3128861763","https://openalex.org/W4288336433","https://openalex.org/W4311917466","https://openalex.org/W6631190155","https://openalex.org/W6757831800","https://openalex.org/W6763566030","https://openalex.org/W6766565677"],"related_works":["https://openalex.org/W2911497689","https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W3010730661","https://openalex.org/W2546503577"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"have":[4],"become":[5],"quite":[6],"popular":[7],"for":[8,61,200],"solving":[9],"many":[10],"different":[11],"tasks":[12],"in":[13,138,168],"remote":[14,47],"sensing":[15,48],"data":[16],"processing.":[17],"The":[18,93],"convolution":[19],"is":[20,91],"a":[21,82,144],"linear":[22],"operation,":[23],"which":[24],"extracts":[25],"features":[26,119],"from":[27,120],"the":[28,39,66,70,101,121,139,148,156],"input":[29,123],"data.":[30,124],"However,":[31],"nonlinear":[32,59,98,157],"operations":[33,56],"are":[34,57],"able":[35],"to":[36,116,160,194],"better":[37],"characterize":[38],"internal":[40],"relationships":[41],"and":[42,76,112,136,162,197],"hidden":[43],"patterns":[44],"within":[45],"complex":[46],"data,":[49],"such":[50,72],"as":[51,73],"hyperspectral":[52],"images":[53],"(HSIs).":[54],"Morphological":[55],"powerful":[58],"transformations":[60],"feature":[62,149],"extraction":[63],"that":[64,181],"preserve":[65],"essential":[67],"characteristics":[68],"of":[69,104,129,147],"image,":[71],"borders,":[74],"shape,":[75],"structural":[77],"information.":[78],"In":[79],"this":[80],"article,":[81],"new":[83],"end-to-end":[84],"morphological":[85,114,126,133],"deep":[86],"learning":[87],"framework":[88],"(called":[89],"MorphConvHyperNet)":[90],"introduced.":[92],"proposed":[94,184],"approach":[95],"efficiently":[96],"models":[97],"information":[99,158],"during":[100],"training":[102],"process":[103],"HSI":[105,122,201],"classification.":[106,202],"Specifically,":[107],"our":[108,182],"method":[109],"includes":[110],"spectral":[111],"spatial":[113],"blocks":[115,127],"extract":[117],"relevant":[118],"These":[125],"consist":[128],"two":[130],"basic":[131],"2-D":[132,196],"operators":[134],"(erosion":[135],"dilation)":[137],"respective":[140],"layers,":[141],"followed":[142],"by":[143],"weighted":[145],"combination":[146],"maps.":[150],"Both":[151],"layers":[152],"can":[153],"successfully":[154],"encode":[155],"related":[159],"shape":[161],"size,":[163],"playing":[164],"an":[165],"important":[166],"role":[167],"classification":[169],"performance.":[170],"Our":[171],"experimental":[172],"results,":[173],"obtained":[174],"on":[175],"five":[176],"widely":[177],"used":[178],"HSIs,":[179],"reveal":[180],"newly":[183],"MorphConvHyperNet":[185],"offers":[186],"comparable":[187],"(and":[188],"even":[189],"superior)":[190],"performance":[191],"when":[192],"compared":[193],"traditional":[195],"3-D":[198],"CNNs":[199]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":27},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}
