{"id":"https://openalex.org/W2900794075","doi":"https://doi.org/10.1109/igarss.2018.8517955","title":"Similarity-Preserving Deep Features for Hyperspectral Image Classification","display_name":"Similarity-Preserving Deep Features for Hyperspectral Image Classification","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2900794075","doi":"https://doi.org/10.1109/igarss.2018.8517955","mag":"2900794075"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517955","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5019995639","display_name":"Weiwei Song","orcid":"https://orcid.org/0000-0001-5089-4127"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Song","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065061505","display_name":"Leyuan Fang","orcid":"https://orcid.org/0000-0003-2351-4461"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leyuan Fang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067097659","display_name":"Shutao Li","orcid":"https://orcid.org/0000-0002-0585-9848"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shutao Li","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.347,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":1,"citation_normalized_percentile":{"value":0.299887,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":62,"max":70},"biblio":{"volume":null,"issue":null,"first_page":"3595","last_page":"3598"},"is_retracted":false,"is_paratext":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":0.9962,"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":0.9773,"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/similarity","display_name":"Similarity (geometry)","score":0.71081865},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.66139597},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5536514}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.82264817},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.734769},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7338199},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7283458},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.71081865},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.66551757},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.66139597},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5536514},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5523652},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.43700612},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43236038},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4251129},{"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":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517955","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":13,"referenced_works":["https://openalex.org/W2004104348","https://openalex.org/W2029316659","https://openalex.org/W2097915756","https://openalex.org/W2103094532","https://openalex.org/W2114819256","https://openalex.org/W2136251662","https://openalex.org/W2162698522","https://openalex.org/W2166923144","https://openalex.org/W2314785379","https://openalex.org/W2464915613","https://openalex.org/W2500751094","https://openalex.org/W2548791488","https://openalex.org/W2792332881"],"related_works":["https://openalex.org/W4313014865","https://openalex.org/W4230131218","https://openalex.org/W3209970181","https://openalex.org/W3034375524","https://openalex.org/W2404757046","https://openalex.org/W2076134148","https://openalex.org/W2072166414","https://openalex.org/W2070598848","https://openalex.org/W2060875994","https://openalex.org/W2044184146"],"abstract_inverted_index":{"Recently,":[0],"deep":[1,22,52,60,71,112],"learning":[2,23,53],"has":[3],"been":[4],"introduced":[5],"to":[6,56,91],"extract":[7],"hierarchical":[8],"features":[9,61,132],"of":[10,31,43,77,96,104],"hyperspectral":[11],"images":[12],"(HSls)":[13],"and":[14,83,99],"achieved":[15],"good":[16],"classification":[17],"performance.":[18],"However,":[19],"the":[20,28,39,58,93,101,111,117,124,127,136,147],"previous":[21],"based":[24,54],"methods":[25],"only":[26],"consider":[27],"semantic":[29],"information":[30],"individual":[32],"pixel,":[33],"which":[34],"cannot":[35],"effectively":[36],"deal":[37],"with":[38],"complex":[40],"spectral-spatial":[41],"characteristic":[42],"HSls.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48,67],"propose":[49],"a":[50,70,85],"novel":[51],"framework":[55],"learn":[57],"similarity-preserving":[59],"(SPDF)":[62],"for":[63,141],"HSI":[64,142],"classification.":[65,143],"Specifically,":[66],"firstly":[68],"introduce":[69],"network":[72,113],"that":[73],"can":[74,119],"take":[75],"pairs":[76,98,106],"image":[78],"patches":[79],"as":[80],"training":[81],"samples,":[82],"then":[84],"loss":[86],"function":[87],"is":[88,114],"elaborately":[89],"designed":[90],"minimize":[92],"feature":[94,102,108],"distance":[95,103],"similar":[97],"maximize":[100],"dissimilar":[105],"in":[107],"space.":[109],"Once":[110],"well":[115],"trained,":[116],"SPDF":[118],"be":[120],"obtained":[121],"by":[122],"propagating":[123],"samples":[125],"through":[126],"trained":[128],"network.":[129],"Finally,":[130],"these":[131],"are":[133],"fed":[134],"into":[135],"support":[137],"vector":[138],"machines":[139],"(SVM)":[140],"Experimental":[144],"results":[145],"demonstrate":[146],"pro-nosed":[148],"method":[149],"outperforms":[150],"other":[151],"competitive":[152],"methods.":[153]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2900794075","counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2024-12-17T16:33:16.768431","created_date":"2018-11-29"}