{"id":"https://openalex.org/W2900704220","doi":"https://doi.org/10.1109/igarss.2018.8519552","title":"Ship Discrimination with Deep Convolutional Neural Networks in Sar Images","display_name":"Ship Discrimination with Deep Convolutional Neural Networks in Sar Images","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2900704220","doi":"https://doi.org/10.1109/igarss.2018.8519552","mag":"2900704220"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8519552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8519552","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/A5100423129","display_name":"Yuanyuan Wang","orcid":"https://orcid.org/0000-0001-7700-7284"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuanyuan Wang","raw_affiliation_strings":["University of Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115076700","display_name":"Chao Wang","orcid":"https://orcid.org/0000-0003-4887-923X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Wang","raw_affiliation_strings":["University of Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100430255","display_name":"Hong Zhang","orcid":"https://orcid.org/0000-0002-0088-8148"},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Zhang","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210128053","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100423129"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":1.3307,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.84984129,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9973999857902527,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9973999857902527,"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/T11698","display_name":"Underwater Acoustics Research","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9957000017166138,"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/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.8709142208099365},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8073101043701172},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7820433378219604},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7717595100402832},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6897968053817749},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5702937245368958},{"id":"https://openalex.org/keywords/azimuth","display_name":"Azimuth","score":0.5559579730033875},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.5348324775695801},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.5211179852485657},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4797457456588745},{"id":"https://openalex.org/keywords/inverse-synthetic-aperture-radar","display_name":"Inverse synthetic aperture radar","score":0.43093812465667725},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.38512012362480164},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3750714063644409},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3481009006500244},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1020149290561676},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08888211846351624}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.8709142208099365},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8073101043701172},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7820433378219604},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7717595100402832},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6897968053817749},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5702937245368958},{"id":"https://openalex.org/C159737794","wikidata":"https://www.wikidata.org/wiki/Q124274","display_name":"Azimuth","level":2,"score":0.5559579730033875},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.5348324775695801},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.5211179852485657},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4797457456588745},{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.43093812465667725},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.38512012362480164},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3750714063644409},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3481009006500244},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1020149290561676},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08888211846351624},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8519552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8519552","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":0.47999998927116394,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1559090148","https://openalex.org/W1686810756","https://openalex.org/W1903029394","https://openalex.org/W1968387716","https://openalex.org/W2061438449","https://openalex.org/W2097117768","https://openalex.org/W2120066054","https://openalex.org/W2126184250","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2395611524","https://openalex.org/W2412588858","https://openalex.org/W2547578938","https://openalex.org/W2564429410","https://openalex.org/W2747165560","https://openalex.org/W2770553941","https://openalex.org/W2774052311","https://openalex.org/W2774985326","https://openalex.org/W2962835968","https://openalex.org/W2964121744","https://openalex.org/W6637373629"],"related_works":["https://openalex.org/W2068843146","https://openalex.org/W2462749609","https://openalex.org/W2540450177","https://openalex.org/W2170580735","https://openalex.org/W1552305638","https://openalex.org/W2112228652","https://openalex.org/W2545123933","https://openalex.org/W1994788526","https://openalex.org/W1915418828","https://openalex.org/W2613451563"],"abstract_inverted_index":{"With":[0],"the":[1,25,41,55,77,109],"advantages":[2],"of":[3,34,43,83,111],"all-time,":[4],"all-weather,":[5],"and":[6,28,76],"wide":[7],"coverage,":[8],"synthetic":[9],"aperture":[10],"radar":[11],"(SAR)":[12],"systems":[13],"are":[14,87],"widely":[15],"used":[16,88],"for":[17],"ship":[18],"detection":[19,42],"to":[20,57,89],"ensure":[21],"marine":[22],"surveillance.":[23],"However,":[24],"azimuth":[26],"ambiguity":[27],"buildings":[29],"exhibit":[30],"similar":[31],"scattering":[32],"mechanisms":[33],"ships,":[35],"which":[36],"cause":[37],"false":[38],"alarms":[39],"in":[40,64],"ships.":[44],"To":[45],"address":[46],"this":[47,65],"problem,":[48],"self-designed":[49],"deep":[50],"convolutional":[51],"neural":[52],"networks":[53],"with":[54],"capability":[56],"automatically":[58],"learn":[59],"discriminative":[60],"features":[61],"is":[62],"applied":[63],"paper.":[66],"Two":[67],"datasets,":[68,107],"including":[69],"one":[70],"dataset":[71],"reconstructed":[72],"from":[73,80],"IEEEDataPort":[74],"SARSHIPDATA":[75],"other":[78],"constructed":[79],"10":[81],"scenes":[82],"Sentinel-1":[84],"SAR":[85],"images,":[86],"evaluate":[90],"our":[91,97,112],"approach.":[92,113],"Experimental":[93],"results":[94],"reveal":[95],"that":[96],"model":[98],"achieves":[99],"more":[100],"than":[101],"95%":[102],"classification":[103],"accuracy":[104],"on":[105],"both":[106],"demonstrating":[108],"effectiveness":[110]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
