{"id":"https://openalex.org/W1971516751","doi":"https://doi.org/10.1109/ijcnn.2014.6889503","title":"Fast ship detection of synthetic aperture radar images via multi-view features and clustering","display_name":"Fast ship detection of synthetic aperture radar images via multi-view features and clustering","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W1971516751","doi":"https://doi.org/10.1109/ijcnn.2014.6889503","mag":"1971516751"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2014.6889503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","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/A5066783502","display_name":"Shigang Wang","orcid":"https://orcid.org/0000-0001-5961-4582"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shigang Wang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, Shaanxi Province, China","Int. Res. Center for Intell. Perception & Comput., Xidian Univ., Xian, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, Shaanxi Province, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Int. Res. Center for Intell. Perception & Comput., Xidian Univ., Xian, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100764373","display_name":"Shuyuan Yang","orcid":"https://orcid.org/0000-0002-4796-5737"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyuan Yang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, Shaanxi Province, China","Int. Res. Center for Intell. Perception & Comput., Xidian Univ., Xian, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, Shaanxi Province, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Int. Res. Center for Intell. Perception & Comput., Xidian Univ., Xian, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053487344","display_name":"Zhixi Feng","orcid":"https://orcid.org/0000-0002-7372-9180"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixi Feng","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, Shaanxi Province, China","Int. Res. Center for Intell. Perception & Comput., Xidian Univ., Xian, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, Shaanxi Province, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Int. Res. Center for Intell. Perception & Comput., Xidian Univ., Xian, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050630882","display_name":"Licheng Jiao","orcid":"https://orcid.org/0000-0003-3354-9617"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Licheng Jiao","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, Shaanxi Province, China","Int. Res. Center for Intell. Perception & Comput., Xidian Univ., Xian, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an, Shaanxi Province, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Int. Res. Center for Intell. Perception & Comput., Xidian Univ., Xian, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5066783502"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.8961,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77299145,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"404","last_page":"410"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9940000176429749,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9836000204086304,"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":0.7888566851615906},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7628254890441895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.727175235748291},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.7047809958457947},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6404672265052795},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5518593788146973},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5318588614463806},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5052056908607483},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.4720802307128906},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46352535486221313},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43802422285079956},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.437349408864975},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42725810408592224}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.7888566851615906},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7628254890441895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.727175235748291},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.7047809958457947},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6404672265052795},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5518593788146973},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5318588614463806},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5052056908607483},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.4720802307128906},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46352535486221313},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43802422285079956},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.437349408864975},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42725810408592224},{"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},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2014.6889503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"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":23,"referenced_works":["https://openalex.org/W1533162639","https://openalex.org/W2011430131","https://openalex.org/W2013451085","https://openalex.org/W2072151149","https://openalex.org/W2079192682","https://openalex.org/W2079735928","https://openalex.org/W2118116104","https://openalex.org/W2119667080","https://openalex.org/W2125593290","https://openalex.org/W2137782143","https://openalex.org/W2142532318","https://openalex.org/W2142740798","https://openalex.org/W2154610955","https://openalex.org/W2160445017","https://openalex.org/W2161522250","https://openalex.org/W2165616753","https://openalex.org/W2542011133","https://openalex.org/W3097983326","https://openalex.org/W4231057059","https://openalex.org/W6668460080","https://openalex.org/W6681136200","https://openalex.org/W6682713193","https://openalex.org/W6729041962"],"related_works":["https://openalex.org/W2545123933","https://openalex.org/W2585813813","https://openalex.org/W2041414401","https://openalex.org/W2042726296","https://openalex.org/W2096748030","https://openalex.org/W3016428515","https://openalex.org/W2160730947","https://openalex.org/W2747205507","https://openalex.org/W2917196883","https://openalex.org/W1908997176"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,109],"novel":[4],"ship":[5],"detection":[6,63],"scheme":[7,150],"in":[8,153],"coastal":[9],"regions":[10,96],"for":[11],"high-resolution":[12],"synthetic":[13],"aperture":[14],"radar":[15],"(SAR)":[16],"imagery":[17],"based":[18,118,127],"on":[19,67,119,128],"prior":[20],"knowledge":[21],"of":[22,93,100,159],"the":[23,43,53,58,85,134,148,160],"different":[24],"properties":[25],"presented":[26],"by":[27],"target":[28,60,70,101],"and":[29,36,51,81,97,105,155],"clutter.":[30],"To":[31],"begin":[32],"with,":[33],"image":[34,55],"segmentation":[35],"land":[37],"masking":[38],"are":[39,46,103,117,138],"applied":[40],"to":[41,48,107,131],"eliminate":[42],"areas":[44,102],"that":[45,147],"unlikely":[47],"contain":[49],"targets":[50,161],"get":[52],"index":[54],"which":[56,77,116],"indicates":[57],"likely":[59,69],"positions.":[61],"Ship":[62],"is":[64,151],"conducted":[65],"only":[66],"these":[68],"positions":[71],"using":[72],"power":[73,99],"ring":[74],"algorithm":[75],"(PR),":[76],"can":[78,156],"avoid":[79],"unnecessary":[80],"exhaustive":[82],"searches.":[83],"In":[84],"discrimination":[86],"stage,":[87],"two":[88],"new":[89],"features":[90],"named":[91],"number":[92],"8":[94],"connected":[95],"average":[98],"proposed":[104,149],"used":[106],"form":[108],"discriminative":[110],"feature":[111],"group.":[112],"Unlike":[113],"most":[114,158],"discriminators,":[115],"supervised":[120],"learning,":[121],"we":[122],"use":[123],"an":[124],"unsupervised":[125],"method":[126],"K-means":[129],"clustering":[130],"deal":[132],"with":[133],"situations":[135],"where":[136],"there":[137],"few":[139,163],"or":[140],"no":[141],"labeled":[142],"samples.":[143],"Experimental":[144],"results":[145],"show":[146],"fast":[152],"speed":[154],"detect":[157],"while":[162],"false":[164],"alarms":[165],"occur.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}