{"id":"https://openalex.org/W3206744951","doi":"https://doi.org/10.1109/igarss47720.2021.9554545","title":"Proposal of PolSAR Land Classification Using Quaternion Convolutional Neural Networks","display_name":"Proposal of PolSAR Land Classification Using Quaternion Convolutional Neural Networks","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3206744951","doi":"https://doi.org/10.1109/igarss47720.2021.9554545","mag":"3206744951"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9554545","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9554545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5028705745","display_name":"Yuya Matsumoto","orcid":"https://orcid.org/0000-0002-6483-5854"},"institutions":[{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]},{"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":true,"raw_author_name":"Yuya Matsumoto","raw_affiliation_strings":["The University of Tokyo,Department of Electrical Engineering and Information Systems,Tokyo,Japan,113-8656"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Department of Electrical Engineering and Information Systems,Tokyo,Japan,113-8656","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080770673","display_name":"Ryo Natsuaki","orcid":"https://orcid.org/0000-0003-2291-4375"},"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"]},{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryo Natsuaki","raw_affiliation_strings":["The University of Tokyo,Department of Electrical Engineering and Information Systems,Tokyo,Japan,113-8656"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Department of Electrical Engineering and Information Systems,Tokyo,Japan,113-8656","institution_ids":["https://openalex.org/I14396692","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"]},{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Hirose","raw_affiliation_strings":["The University of Tokyo,Department of Electrical Engineering and Information Systems,Tokyo,Japan,113-8656"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Department of Electrical Engineering and Information Systems,Tokyo,Japan,113-8656","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028705745"],"corresponding_institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0700068,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":null,"first_page":"403","last_page":"406"},"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":1.0,"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":1.0,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9975000023841858,"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":0.9918000102043152,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/quaternion","display_name":"Quaternion","score":0.9173023700714111},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7162747979164124},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.658431887626648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6334476470947266},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6210622787475586},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5872222781181335},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5439971685409546},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4791116714477539},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.428888738155365},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21677303314208984},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.1026553213596344},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.05553427338600159}],"concepts":[{"id":"https://openalex.org/C200127275","wikidata":"https://www.wikidata.org/wiki/Q173853","display_name":"Quaternion","level":2,"score":0.9173023700714111},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7162747979164124},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.658431887626648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6334476470947266},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6210622787475586},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5872222781181335},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5439971685409546},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4791116714477539},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.428888738155365},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21677303314208984},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.1026553213596344},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.05553427338600159},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss47720.2021.9554545","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9554545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G6905829485","display_name":null,"funder_award_id":"18H04105","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"},{"id":"https://openalex.org/G8261081478","display_name":null,"funder_award_id":"1154 (AH)","funder_id":"https://openalex.org/F4320334900","funder_display_name":"Japan Aerospace Exploration Agency"}],"funders":[{"id":"https://openalex.org/F4320320212","display_name":"Japan Society for the Promotion of Science London","ror":"https://ror.org/02m7axw05"},{"id":"https://openalex.org/F4320334900","display_name":"Japan Aerospace Exploration Agency","ror":"https://ror.org/059yhyy33"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1700035086","https://openalex.org/W1989757000","https://openalex.org/W2019601122","https://openalex.org/W2097272115","https://openalex.org/W2132012856","https://openalex.org/W2133989913","https://openalex.org/W2141424348","https://openalex.org/W2559324447","https://openalex.org/W2766299269","https://openalex.org/W6637501666"],"related_works":["https://openalex.org/W3127350447","https://openalex.org/W3108700312","https://openalex.org/W4225472102","https://openalex.org/W2382948573","https://openalex.org/W2887325221","https://openalex.org/W2084651007","https://openalex.org/W2184550115","https://openalex.org/W2964954556","https://openalex.org/W2357412443","https://openalex.org/W3025407325"],"abstract_inverted_index":{"This":[0,34],"paper":[1],"proposes":[2],"a":[3,54],"quaternion":[4,21,76],"convolutional":[5],"neural":[6],"network":[7],"(QCNN)":[8],"for":[9],"PolSAR":[10],"land":[11],"classification.":[12],"The":[13,24],"QCNN":[14,25,39,62],"learns":[15,26],"spatial":[16,79],"features":[17,80],"of":[18,30,44,51],"polarization":[19],"with":[20,47],"convo-lutional":[22],"layers.":[23],"relationship":[27],"between":[28],"components":[29],"input":[31],"three-dimensional":[32],"vectors.":[33],"property":[35],"also":[36,71],"makes":[37],"the":[38,48,61,75],"map":[40],"inputs":[41],"to":[42],"space":[43],"higher":[45],"dimension":[46],"same":[49],"number":[50],"parameters":[52],"than":[53,67],"real-valued":[55],"CNN":[56],"(RVCNN).":[57],"In":[58],"our":[59],"experiments,":[60],"shows":[63],"better":[64],"classification":[65],"performance":[66],"conventional":[68],"networks.":[69],"We":[70],"present":[72],"visually":[73],"that":[74],"kernels":[77],"extract":[78],"by":[81],"quaternionic":[82],"convolution.":[83]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}