{"id":"https://openalex.org/W2770727026","doi":"https://doi.org/10.1109/tgrs.2017.2768619","title":"Unsupervised Fine Land Classification Using Quaternion Autoencoder-Based Polarization Feature Extraction and Self-Organizing Mapping","display_name":"Unsupervised Fine Land Classification Using Quaternion Autoencoder-Based Polarization Feature Extraction and Self-Organizing Mapping","publication_year":2017,"publication_date":"2017-11-22","ids":{"openalex":"https://openalex.org/W2770727026","doi":"https://doi.org/10.1109/tgrs.2017.2768619","mag":"2770727026"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2017.2768619","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2017.2768619","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5100441147","display_name":"Hyunsoo Kim","orcid":"https://orcid.org/0000-0002-5194-0372"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hyunsoo Kim","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-5194-0372","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075783559","display_name":"Akira Hirose","orcid":"https://orcid.org/0000-0002-6936-9733"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Hirose","raw_affiliation_strings":["Department of Electrical and Electronic Engineering and the Department of Bioengineering, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-6936-9733","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering and the Department of Bioengineering, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":103.9603,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.99846601,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"56","issue":"3","first_page":"1839","last_page":"1851"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9945999979972839,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7509647607803345},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.711494505405426},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6668657064437866},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6277488470077515},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5562461018562317},{"id":"https://openalex.org/keywords/self-organizing-map","display_name":"Self-organizing map","score":0.5538085699081421},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.5295565724372864},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.4949116110801697},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.488946795463562},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.44775694608688354},{"id":"https://openalex.org/keywords/quaternion","display_name":"Quaternion","score":0.4396604299545288},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4340885281562805},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38088804483413696},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3594464957714081},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1740490198135376},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1488352119922638},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0961950421333313}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7509647607803345},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.711494505405426},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6668657064437866},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6277488470077515},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5562461018562317},{"id":"https://openalex.org/C111168008","wikidata":"https://www.wikidata.org/wiki/Q1136838","display_name":"Self-organizing map","level":3,"score":0.5538085699081421},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.5295565724372864},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.4949116110801697},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.488946795463562},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.44775694608688354},{"id":"https://openalex.org/C200127275","wikidata":"https://www.wikidata.org/wiki/Q173853","display_name":"Quaternion","level":2,"score":0.4396604299545288},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4340885281562805},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38088804483413696},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3594464957714081},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1740490198135376},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1488352119922638},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0961950421333313},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2017.2768619","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2017.2768619","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.5},{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4099999964237213}],"awards":[{"id":"https://openalex.org/G439518252","display_name":"Construction of the engineering framework of phasor quaternion neural networks in adaptive electromagnetic-wave information processing","funder_award_id":"18H04105","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G6226354307","display_name":"Quaternion neural networks to deal with polarization information in electromagnetic wave and lightwave","funder_award_id":"15H02756","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320327368","display_name":"KDDI Foundation","ror":"https://ror.org/005914142"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1639731067","https://openalex.org/W1696305814","https://openalex.org/W1964141569","https://openalex.org/W1974141535","https://openalex.org/W1982866705","https://openalex.org/W1984082165","https://openalex.org/W1985029143","https://openalex.org/W1989757000","https://openalex.org/W1995905029","https://openalex.org/W2020971112","https://openalex.org/W2054738262","https://openalex.org/W2079454091","https://openalex.org/W2097272115","https://openalex.org/W2112130876","https://openalex.org/W2113156691","https://openalex.org/W2114578114","https://openalex.org/W2116319373","https://openalex.org/W2130269771","https://openalex.org/W2132012856","https://openalex.org/W2133989913","https://openalex.org/W2141424348","https://openalex.org/W2145882662","https://openalex.org/W2150059023","https://openalex.org/W2154830216","https://openalex.org/W2167309519","https://openalex.org/W2171056811","https://openalex.org/W2306802236","https://openalex.org/W2337944562","https://openalex.org/W2529993082","https://openalex.org/W2595106450","https://openalex.org/W3036543524"],"related_works":["https://openalex.org/W2594436708","https://openalex.org/W4360994128","https://openalex.org/W2769441402","https://openalex.org/W3086240734","https://openalex.org/W2951850672","https://openalex.org/W2789476480","https://openalex.org/W2997921738","https://openalex.org/W2965146396","https://openalex.org/W2770818364","https://openalex.org/W150043153"],"abstract_inverted_index":{"We":[0,167],"propose":[1],"an":[2,127],"unsupervised":[3,18,128],"polarimetric":[4],"synthetic":[5],"aperture":[6],"radar":[7],"(PolSAR)":[8],"land":[9,36,68,102,141],"classification":[10,37,62,103],"system":[11,80],"consisting":[12],"of":[13,16,32,42,67,89,172,175],"a":[14,22,26,40,64,75,131],"series":[15],"two":[17],"neural":[19],"networks,":[20],"namely,":[21],"quaternion":[23,27,76,124],"autoencoder":[24],"and":[25,138,152,155,163],"self-organizing":[28],"map":[29],"(SOM).":[30],"Most":[31],"the":[33,56,86,98,107,117,123,170,176,179],"existing":[34],"PolSAR":[35,90],"systems":[38],"use":[39],"set":[41],"feature":[43,82],"information":[44,83,99],"that":[45,97,116],"humans":[46],"designed":[47],"beforehand.":[48],"However,":[49],"such":[50],"methods":[51],"will":[52],"face":[53],"limitations":[54],"in":[55,126,178],"near":[57],"future":[58],"when":[59],"we":[60,95,114,133],"expect":[61],"into":[63,149,160],"large":[65],"number":[66],"categories":[69],"recognizable":[70],"to":[71],"humans.":[72],"By":[73],"using":[74],"autoencoder,":[77],"our":[78],"proposed":[79],"extracts":[81],"based":[84],"on":[85],"natural":[87],"distribution":[88],"features.":[91],"In":[92],"this":[93],"paper,":[94],"confirm":[96],"necessary":[100],"for":[101],"is":[104,111],"extracted":[105,118],"as":[106],"features":[108,119,177],"while":[109],"noise":[110],"filtered.":[112],"Then,":[113],"show":[115],"are":[120,147,158],"classified":[121],"by":[122],"SOM":[125,180],"manner.":[129],"As":[130],"result,":[132],"can":[134],"discover":[135],"even":[136],"new":[137],"more":[139],"detailed":[140],"categories.":[142],"For":[143],"example,":[144],"town":[145],"areas":[146,151,157],"divided":[148],"residential":[150],"factory":[153],"sites,":[154],"grass":[156,165],"subcategorized":[159],"furrowed":[161],"farmlands":[162],"flat":[164],"areas.":[166],"also":[168],"examine":[169],"realization":[171],"topographic":[173],"mapping":[174],"space.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":1}],"updated_date":"2026-08-29T07:29:34.045763","created_date":"2025-10-10T00:00:00"}
