{"id":"https://openalex.org/W2901055435","doi":"https://doi.org/10.3390/rs10111799","title":"Automatic Ship Detection Using the Artificial Neural Network and Support Vector Machine from X-Band Sar Satellite Images","display_name":"Automatic Ship Detection Using the Artificial Neural Network and Support Vector Machine from X-Band Sar Satellite Images","publication_year":2018,"publication_date":"2018-11-13","ids":{"openalex":"https://openalex.org/W2901055435","doi":"https://doi.org/10.3390/rs10111799","mag":"2901055435"},"language":"en","primary_location":{"id":"doi:10.3390/rs10111799","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10111799","pdf_url":"https://www.mdpi.com/2072-4292/10/11/1799/pdf?version=1542106504","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/10/11/1799/pdf?version=1542106504","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101025244","display_name":"Jeong-in Hwang","orcid":null},"institutions":[{"id":"https://openalex.org/I124633538","display_name":"University of Seoul","ror":"https://ror.org/05en5nh73","country_code":"KR","type":"education","lineage":["https://openalex.org/I124633538"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jeong-In Hwang","raw_affiliation_strings":["Department of Geoinformatics, University of Seoul, Seoul 02504, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geoinformatics, University of Seoul, Seoul 02504, Korea","institution_ids":["https://openalex.org/I124633538"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040012035","display_name":"Hyung-Sup Jung","orcid":"https://orcid.org/0000-0003-2335-8438"},"institutions":[{"id":"https://openalex.org/I124633538","display_name":"University of Seoul","ror":"https://ror.org/05en5nh73","country_code":"KR","type":"education","lineage":["https://openalex.org/I124633538"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyung-Sup Jung","raw_affiliation_strings":["Department of Geoinformatics, University of Seoul, Seoul 02504, Korea"],"raw_orcid":"https://orcid.org/0000-0003-2335-8438","affiliations":[{"raw_affiliation_string":"Department of Geoinformatics, University of Seoul, Seoul 02504, Korea","institution_ids":["https://openalex.org/I124633538"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5040012035"],"corresponding_institution_ids":["https://openalex.org/I124633538"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":48.4172,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.99616015,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"10","issue":"11","first_page":"1799","last_page":"1799"},"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":0.9975000023841858,"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"}},"topics":[{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and 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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9940999746322632,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9932000041007996,"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/support-vector-machine","display_name":"Support vector machine","score":0.7552789449691772},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7421050071716309},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6703396439552307},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6648918390274048},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.5205903053283691},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4890950322151184},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.47050541639328003},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.46243107318878174},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45238426327705383},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.45176345109939575},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37775471806526184},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3775196075439453},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.33557790517807007},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09789440035820007},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07344460487365723}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7552789449691772},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7421050071716309},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6703396439552307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6648918390274048},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.5205903053283691},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4890950322151184},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.47050541639328003},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.46243107318878174},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45238426327705383},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.45176345109939575},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37775471806526184},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3775196075439453},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.33557790517807007},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09789440035820007},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07344460487365723},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs10111799","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10111799","pdf_url":"https://www.mdpi.com/2072-4292/10/11/1799/pdf?version=1542106504","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fe5e2ea974b240ccbdc158da9dc78a19","is_oa":true,"landing_page_url":"https://doaj.org/article/fe5e2ea974b240ccbdc158da9dc78a19","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 10, Iss 11, p 1799 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/10/11/1799/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs10111799","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs10111799","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10111799","pdf_url":"https://www.mdpi.com/2072-4292/10/11/1799/pdf?version=1542106504","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G7446930633","display_name":null,"funder_award_id":"NRF-2018M1A3A3A02066008","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2901055435.pdf"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W147446552","https://openalex.org/W1566144858","https://openalex.org/W1932600547","https://openalex.org/W1969985137","https://openalex.org/W1970782782","https://openalex.org/W1995341919","https://openalex.org/W2001546612","https://openalex.org/W2002016471","https://openalex.org/W2006467595","https://openalex.org/W2020880265","https://openalex.org/W2021917018","https://openalex.org/W2023290904","https://openalex.org/W2028070629","https://openalex.org/W2034875816","https://openalex.org/W2079454091","https://openalex.org/W2089564362","https://openalex.org/W2096223773","https://openalex.org/W2098115576","https://openalex.org/W2100503224","https://openalex.org/W2104763670","https://openalex.org/W2109257156","https://openalex.org/W2117294245","https://openalex.org/W2119391693","https://openalex.org/W2120066054","https://openalex.org/W2121150791","https://openalex.org/W2125384310","https://openalex.org/W2127172377","https://openalex.org/W2130762895","https://openalex.org/W2131521640","https://openalex.org/W2132996847","https://openalex.org/W2133361363","https://openalex.org/W2133504205","https://openalex.org/W2138957397","https://openalex.org/W2151554017","https://openalex.org/W2153094283","https://openalex.org/W2153635508","https://openalex.org/W2153683394","https://openalex.org/W2164383685","https://openalex.org/W2165090887","https://openalex.org/W2463404136","https://openalex.org/W2465660745","https://openalex.org/W2588453093","https://openalex.org/W2588505606","https://openalex.org/W2608595117","https://openalex.org/W2747165560","https://openalex.org/W2755447448","https://openalex.org/W2770553941","https://openalex.org/W2781693345","https://openalex.org/W2783266131","https://openalex.org/W2893774456","https://openalex.org/W2945103936","https://openalex.org/W3152368928","https://openalex.org/W4239510810","https://openalex.org/W6680396984","https://openalex.org/W6682862474","https://openalex.org/W6747105869","https://openalex.org/W6755352000","https://openalex.org/W6762456866"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W3135697610","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W148178222","https://openalex.org/W1647606319","https://openalex.org/W2922442631","https://openalex.org/W2104657898","https://openalex.org/W4390494008"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"an":[3,104],"automatic":[4],"ship":[5,63,127,254],"detection":[6,251],"method":[7,145,248],"using":[8,27,146,216],"the":[9,31,40,47,89,93,110,113,119,122,136,140,143,169,178,186,199,205,217,227,231,246,250],"artificial":[10],"neural":[11],"network":[12],"(ANN)":[13],"and":[14,44,65,82,92,118,154,161,176,188,207,220],"support":[15],"vector":[16],"machine":[17,28,190,200],"(SVM)":[18],"from":[19,168,226,256,267],"X-band":[20,147,170,257],"SAR":[21,149,171,258],"satellite":[22],"images":[23,150,259],"is":[24],"proposed.":[25],"When":[26],"learning":[29,191,201],"techniques,":[30,73],"most":[32,126,241,253],"important":[33],"points":[34],"to":[35,87,100,108,223],"consider":[36],"are":[37],"(i)":[38,61],"defining":[39],"proper":[41],"input":[42,57,183],"neurons":[43,59,184],"(ii)":[45,66],"selecting":[46],"correct":[48],"training":[49],"data.":[50],"We":[51,138],"focused":[52],"on":[53],"generating":[54],"two":[55],"optimal":[56,210],"data":[58],"that":[60,245],"strengthened":[62],"targets":[64,255],"mitigated":[67],"noise":[68],"effects":[69],"by":[70,215],"image":[71,105],"processing":[72],"including":[74,130,151],"median":[75,80,94],"filtering,":[76],"multi-looking,":[77],"etc.":[78],"The":[79],"filter":[81,95],"multi-look":[83],"operations":[84],"were":[85,133,166,180,213],"used":[86,99,181,222],"reduce":[88],"background":[90],"noise,":[91],"operation":[96],"was":[97,236],"also":[98],"remove":[101],"ships":[102,117,225],"in":[103,106,135,240],"order":[107],"maximize":[109],"difference":[111,124,159,164],"between":[112],"pixel":[114],"values":[115,212],"of":[116,142,233,252,264],"sea.":[120],"Through":[121],"root-mean-square":[123],"calculation,":[125],"targets,":[128],"even":[129],"small":[131],"ships,":[132],"emphasized":[134],"images.":[137,156],"tested":[139],"performance":[141],"proposed":[144,247],"high-resolution":[148],"COSMO-SkyMed,":[152],"KOMPSAT-5,":[153],"TerraSAR-X":[155],"An":[157],"intensity":[158],"map":[160,165],"a":[162,261],"texture":[163],"extracted":[167],"single-look":[172],"complex":[173],"(SLC)":[174],"images,":[175],"then,":[177],"maps":[179,197],"as":[182],"for":[185],"ANN":[187,206],"SVM":[189,208],"techniques.":[192,202],"Finally,":[193],"we":[194],"created":[195],"ship-probability":[196,228],"through":[198],"To":[203],"validate":[204],"results,":[209],"threshold":[211],"obtained":[214],"statistical":[218],"approach":[219],"then":[221],"identify":[224],"maps.":[229],"Consequently,":[230],"level":[232],"recall":[234],"achieved":[235],"greater":[237],"than":[238],"90%":[239],"cases.":[242],"This":[243],"means":[244],"enables":[249],"with":[260],"reduced":[262],"number":[263],"false":[265],"detections":[266],"negative":[268],"effects.":[269]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":7}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}