{"id":"https://openalex.org/W3205482641","doi":"https://doi.org/10.1109/igarss47720.2021.9554697","title":"SAR Ship Detection Based on an Improved Faster R-CNN Using Deformable Convolution","display_name":"SAR Ship Detection Based on an Improved Faster R-CNN Using Deformable Convolution","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3205482641","doi":"https://doi.org/10.1109/igarss47720.2021.9554697","mag":"3205482641"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9554697","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9554697","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","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/A5025474158","display_name":"Xiao Ke","orcid":"https://orcid.org/0000-0001-5895-2766"},"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":true,"raw_author_name":"Xiao Ke","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385993","display_name":"Xiaoling Zhang","orcid":"https://orcid.org/0000-0003-2343-3055"},"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":"Xiaoling Zhang","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082458788","display_name":"Tianwen Zhang","orcid":null},"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":"Tianwen Zhang","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066834799","display_name":"Junren Shi","orcid":"https://orcid.org/0000-0002-0385-3055"},"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":"Jun Shi","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080246113","display_name":"Shunjun Wei","orcid":"https://orcid.org/0000-0001-8091-9540"},"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":"Shunjun Wei","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5025474158"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":2.6899,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.91903595,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3565","last_page":"3568"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9983999729156494,"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":0.9983999729156494,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9898999929428101,"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/convolution","display_name":"Convolution (computer science)","score":0.8894001841545105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7255635261535645},{"id":"https://openalex.org/keywords/geometric-transformation","display_name":"Geometric transformation","score":0.6868645548820496},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6714770793914795},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.6527977585792542},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.601201057434082},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4938121736049652},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48581647872924805},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4253509044647217},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39169132709503174},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34537172317504883},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23661544919013977},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.07517343759536743}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.8894001841545105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7255635261535645},{"id":"https://openalex.org/C56435381","wikidata":"https://www.wikidata.org/wiki/Q1196371","display_name":"Geometric transformation","level":3,"score":0.6868645548820496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6714770793914795},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.6527977585792542},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.601201057434082},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4938121736049652},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48581647872924805},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4253509044647217},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39169132709503174},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34537172317504883},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23661544919013977},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.07517343759536743},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss47720.2021.9554697","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9554697","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W2593852290","https://openalex.org/W2747165560","https://openalex.org/W2774244034","https://openalex.org/W2902303185","https://openalex.org/W2961699889","https://openalex.org/W2966926453","https://openalex.org/W3038948729","https://openalex.org/W6637373629"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2366906938","https://openalex.org/W2349391998","https://openalex.org/W4205655149","https://openalex.org/W2000775715","https://openalex.org/W2964954556","https://openalex.org/W3019910406","https://openalex.org/W3205482641","https://openalex.org/W2393943770","https://openalex.org/W2765965840"],"abstract_inverted_index":{"With":[0],"the":[1,19,33,92,99,106,110,132],"rise":[2],"of":[3,21,36,91,102],"Deep":[4],"Learning":[5],"(DL),":[6],"numerous":[7],"DL-based":[8],"SAR":[9,67,112],"ship":[10,68],"detectors,":[11],"represented":[12],"by":[13,61],"Faster":[14,59,78,121,134],"R-CNN,":[15],"is":[16,48],"constantly":[17],"breaking":[18],"record":[20],"detection":[22],"accuracy.":[23],"However,":[24],"these":[25],"detectors":[26],"still":[27],"face":[28],"huge":[29],"challenges":[30],"in":[31,77],"modeling":[32],"geometric":[34,100],"transformation":[35,101],"shape-changeable":[37,103],"ships,":[38],"due":[39],"to":[40,51,96],"their":[41],"used":[42],"conventional":[43,73],"convolution":[44,64,75,82,94],"kernels":[45,65,76],"whose":[46],"structure":[47],"fixed.":[49],"Therefore,":[50],"address":[52],"this":[53],"problem,":[54],"we":[55],"propose":[56],"an":[57],"improved":[58,120],"R-CNN":[60,79,122],"using":[62],"deformable":[63,81],"for":[66],"detection.":[69],"We":[70],"substitute":[71],"some":[72],"shape-changeless":[74],"with":[80],"ones":[83],"that":[84,118],"can":[85],"adaptively":[86],"learn":[87],"additional":[88],"2-D":[89],"offsets":[90],"raw":[93,133],"kernels,":[95],"better":[97],"model":[98],"ships.":[104],"Finally,":[105],"experimental":[107],"results":[108],"on":[109],"open":[111],"Ship":[113],"Detection":[114],"Dataset":[115],"(SSDD)":[116],"reveal":[117],"our":[119],"achieves":[123],"a":[124],"2.02%":[125],"mean":[126],"Average":[127],"Precision":[128],"(mAP)":[129],"improvement":[130],"than":[131],"R-CNN.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":9}],"updated_date":"2026-01-23T23:20:30.427331","created_date":"2025-10-10T00:00:00"}