{"id":"https://openalex.org/W2901096730","doi":"https://doi.org/10.1109/igarss.2018.8518966","title":"Comparative Study of Feature Extraction Approaches for Ship Classification in Moderate-Resolution SAR Imagery","display_name":"Comparative Study of Feature Extraction Approaches for Ship Classification in Moderate-Resolution SAR Imagery","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901096730","doi":"https://doi.org/10.1109/igarss.2018.8518966","mag":"2901096730"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518966","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","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/A5074292246","display_name":"Shreya Sharma","orcid":"https://orcid.org/0000-0001-7547-8867"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shreya Sharma","raw_affiliation_strings":["Data Science Research Laboratories, NEC Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Laboratories, NEC Corporation","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024726607","display_name":"Kenta Senzaki","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kenta Senzaki","raw_affiliation_strings":["Data Science Research Laboratories, NEC Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Laboratories, NEC Corporation","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001400226","display_name":"Hirofumi Aoki","orcid":"https://orcid.org/0000-0002-4930-0181"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hirofumi Aoki","raw_affiliation_strings":["Data Science Research Laboratories, NEC Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Laboratories, NEC Corporation","institution_ids":["https://openalex.org/I118347220"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.212,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.57434709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"313","issue":null,"first_page":"6995","last_page":"6998"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9943000078201294,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9943000078201294,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9904999732971191,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.989300012588501,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7546901106834412},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7340495586395264},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7193830013275146},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6734343767166138},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6354093551635742},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.600415825843811},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5545107126235962},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5278054475784302},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5189895033836365},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.44728392362594604},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4450932741165161},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.42518121004104614},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.36746424436569214},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32055041193962097},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3071846663951874},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24215680360794067},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1025221049785614}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7546901106834412},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7340495586395264},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193830013275146},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6734343767166138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6354093551635742},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.600415825843811},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5545107126235962},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5278054475784302},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5189895033836365},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.44728392362594604},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4450932741165161},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.42518121004104614},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36746424436569214},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32055041193962097},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3071846663951874},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24215680360794067},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1025221049785614},{"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":[{"id":"doi:10.1109/igarss.2018.8518966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518966","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/14","display_name":"Life below water"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1998489088","https://openalex.org/W2019178979","https://openalex.org/W2056490079","https://openalex.org/W2100495367","https://openalex.org/W2167220279","https://openalex.org/W2313666604","https://openalex.org/W2539825053","https://openalex.org/W2751615339"],"related_works":["https://openalex.org/W4210966920","https://openalex.org/W2550009779","https://openalex.org/W1975547468","https://openalex.org/W2804627982","https://openalex.org/W2001679188","https://openalex.org/W4205493345","https://openalex.org/W2196068029","https://openalex.org/W2016342027","https://openalex.org/W2888859519","https://openalex.org/W1538678705"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,24],"comparative":[4],"study":[5],"of":[6,42,71,102,136],"existing":[7,43],"feature":[8,37,82],"extraction":[9,38,83],"approaches":[10],"for":[11,104],"ship":[12,34,106],"classification":[13,22,107,122,135],"in":[14,27,121,134],"moderate-resolution":[15,75],"synthetic":[16],"aperture":[17],"radar":[18],"(SAR)":[19],"images.":[20,48,76],"Ship":[21],"is":[23,39,55,97],"key":[25],"functionality":[26],"many":[28],"maritime":[29,50],"surveillance":[30],"applications.":[31],"For":[32,49],"efficient":[33],"classification,":[35],"appropriate":[36],"crucial.":[40],"Most":[41],"studies":[44],"have":[45],"used":[46],"high-resolution":[47],"surveillance,":[51],"however,":[52],"wide-area":[53],"coverage":[54],"essential":[56],"whereas":[57],"it":[58],"inevitably":[59],"reduces":[60],"the":[61,69,100],"spatial":[62],"resolution.":[63],"In":[64],"this":[65],"paper,":[66],"we":[67],"evaluate":[68],"applicability":[70],"representative":[72],"methods":[73,79],"to":[74],"The":[77,95,112],"evaluated":[78],"are":[80],"hand-crafted":[81],"(HCF),":[84],"principal":[85],"component":[86],"analysis":[87],"(PCA)":[88],"and":[89,110,119,126],"autoencoder":[90],"(AE)":[91],"based":[92],"on":[93,99],"neural-network.":[94],"evaluation":[96],"done":[98],"basis":[101],"accuracy":[103,123],"two-class":[105],"into":[108],"tanker":[109],"cargo.":[111],"experiments":[113],"demonstrate":[114],"that":[115],"AE":[116,130],"outperforms":[117],"HCF":[118],"PCA":[120],"by":[124],"7.4%":[125],"2.6%,":[127],"respectively.":[128],"Furthermore,":[129],"performs":[131],"best":[132],"even":[133],"challenging":[137],"cases":[138],"such":[139],"as":[140],"small":[141],"ships.":[142]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}