{"id":"https://openalex.org/W3131228544","doi":"https://doi.org/10.1109/igarss39084.2020.9324196","title":"An Integrated Method of Ship Detection and Recognition in Sar Images based on Deep Learning","display_name":"An Integrated Method of Ship Detection and Recognition in Sar Images based on Deep Learning","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3131228544","doi":"https://doi.org/10.1109/igarss39084.2020.9324196","mag":"3131228544"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9324196","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103162320","display_name":"Zesheng Hou","orcid":"https://orcid.org/0000-0002-9963-3427"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zesheng Hou","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061245960","display_name":"Zongyong Cui","orcid":"https://orcid.org/0000-0003-1155-786X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongyong Cui","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019411747","display_name":"Zongjie Cao","orcid":"https://orcid.org/0000-0002-0117-9087"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongjie Cao","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003057872","display_name":"Nengyuan Liu","orcid":"https://orcid.org/0000-0002-2827-3321"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nengyuan Liu","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1225","last_page":"1228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9970999956130981,"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":0.9970999956130981,"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":0.9890999794006348,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9592000246047974,"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/computer-science","display_name":"Computer science","score":0.7353627681732178},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7259513139724731},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7221509218215942},{"id":"https://openalex.org/keywords/subnetwork","display_name":"Subnetwork","score":0.6610724925994873},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.5602549910545349},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4841528534889221},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.43297770619392395},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43240296840667725},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4217676520347595},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.31630411744117737}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7353627681732178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7259513139724731},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7221509218215942},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.6610724925994873},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.5602549910545349},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4841528534889221},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.43297770619392395},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43240296840667725},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4217676520347595},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.31630411744117737},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9324196","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1014185754","display_name":null,"funder_award_id":"SAST 2018-079","funder_id":"https://openalex.org/F4320335011","funder_display_name":"School of Aerospace Science and Technology"},{"id":"https://openalex.org/G3188930348","display_name":null,"funder_award_id":"61801098,61971101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335011","display_name":"School of Aerospace Science and Technology","ror":"https://ror.org/05s92vm98"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2144158572","https://openalex.org/W2565639579","https://openalex.org/W2752782242","https://openalex.org/W2767185544","https://openalex.org/W2794681092","https://openalex.org/W2901930404","https://openalex.org/W2961699889","https://openalex.org/W2963351448","https://openalex.org/W2964165364","https://openalex.org/W2974097168","https://openalex.org/W2988947442","https://openalex.org/W6756647740","https://openalex.org/W6770240466"],"related_works":["https://openalex.org/W3137365474","https://openalex.org/W2886347302","https://openalex.org/W2784759481","https://openalex.org/W1545594509","https://openalex.org/W2540523933","https://openalex.org/W3038591045","https://openalex.org/W3130755980","https://openalex.org/W2540650467","https://openalex.org/W4380446815","https://openalex.org/W2773828237"],"abstract_inverted_index":{"Ship":[0,48],"target":[1,28,49,84],"interpretation":[2,50],"in":[3,11,13,51,94],"SAR":[4,20,44,52],"images":[5,53],"has":[6],"become":[7],"an":[8,79],"important":[9],"topic":[10],"research":[12],"recent":[14],"years.":[15],"With":[16],"the":[17,23,72,99,102,104,111,117,126,130],"improvement":[18],"of":[19,25,36,75,82,101,116,129],"image":[21,45],"resolution,":[22],"performance":[24],"traditional":[26,76],"automatic":[27],"recognition":[29,87],"(ATR)":[30],"method":[31,81,120],"decreases":[32],"gradually.":[33],"The":[34,114],"emergence":[35],"deep":[37,56,90],"network":[38,91],"provides":[39],"a":[40],"new":[41],"solution":[42],"for":[43],"ship":[46,83,131],"interpretation.":[47],"based":[54,88],"on":[55,71,89],"learning":[57],"is":[58,92,108,121],"divided":[59],"into":[60],"detection":[61,85],"and":[62,86,125],"classification,":[63],"but":[64],"they":[65],"haven't":[66],"been":[67],"integrated":[68],"yet.":[69],"Based":[70],"process":[73],"flow":[74],"ATR":[77],"system,":[78],"integration":[80,119],"proposed":[93,118],"this":[95],"paper.":[96],"And":[97],"at":[98],"end":[100],"network,":[103],"squeeze-and-excitation":[105],"(SE)":[106],"module":[107],"added":[109],"to":[110],"classification":[112,127],"subnetwork.":[113],"effectiveness":[115],"verified":[122],"by":[123,133],"experiments,":[124],"accuracy":[128],"increased":[132],"3.7%":[134],"after":[135],"adding":[136],"SE":[137],"module.":[138]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}