{"id":"https://openalex.org/W2985464328","doi":"https://doi.org/10.1109/igarss.2019.8898068","title":"A Level Set Based Method for Land Masking in Ship Detection Using SAR Images","display_name":"A Level Set Based Method for Land Masking in Ship Detection Using SAR Images","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2985464328","doi":"https://doi.org/10.1109/igarss.2019.8898068","mag":"2985464328"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8898068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8898068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 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/A5100389366","display_name":"Ziwei Wang","orcid":"https://orcid.org/0000-0001-9225-8495"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziwei Wang","raw_affiliation_strings":["School of Electronics and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631304","display_name":"Wei Yang","orcid":"https://orcid.org/0000-0002-2014-8120"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Yang","raw_affiliation_strings":["School of Electronics and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100332980","display_name":"Jie Chen","orcid":"https://orcid.org/0000-0002-9370-3965"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Chen","raw_affiliation_strings":["School of Electronics and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100440503","display_name":"Chunsheng Li","orcid":"https://orcid.org/0000-0001-9050-9078"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunsheng Li","raw_affiliation_strings":["School of Electronics and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3888","last_page":"3891"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9886999726295471,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9886999726295471,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9840999841690063,"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/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.816268801689148},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.7806275486946106},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7624998688697815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7130149602890015},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5710033178329468},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.5501804351806641},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.5458777546882629},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5030249953269958},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47585031390190125},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4511779546737671},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.4403313100337982},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4291401207447052},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4114503264427185},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.41053909063339233},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3772197961807251},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3642043173313141},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.3188512325286865},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12123224139213562}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.816268801689148},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.7806275486946106},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7624998688697815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7130149602890015},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5710033178329468},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.5501804351806641},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.5458777546882629},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5030249953269958},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47585031390190125},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4511779546737671},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.4403313100337982},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4291401207447052},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4114503264427185},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.41053909063339233},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3772197961807251},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3642043173313141},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.3188512325286865},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12123224139213562},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","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},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8898068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8898068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.8799999952316284}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1981055814","https://openalex.org/W2027007720","https://openalex.org/W2038182754","https://openalex.org/W2090217374","https://openalex.org/W2114666101","https://openalex.org/W2132005247","https://openalex.org/W2395611524","https://openalex.org/W2560703724","https://openalex.org/W2793141496"],"related_works":["https://openalex.org/W3013122649","https://openalex.org/W3038948729","https://openalex.org/W3159745752","https://openalex.org/W2368147775","https://openalex.org/W2896392990","https://openalex.org/W2292705224","https://openalex.org/W2958528535","https://openalex.org/W3210394105","https://openalex.org/W3014034920","https://openalex.org/W3210613462","https://openalex.org/W2182094895","https://openalex.org/W2786355301","https://openalex.org/W1596965588","https://openalex.org/W2368438077","https://openalex.org/W3167169752","https://openalex.org/W2029873059","https://openalex.org/W2326128361","https://openalex.org/W2126077476","https://openalex.org/W3018466345","https://openalex.org/W2171193731"],"abstract_inverted_index":{"This":[0],"paper":[1,120],"presents":[2],"an":[3],"efficient":[4],"approach":[5],"to":[6,36,51,78,91,94,137],"obtain":[7],"land":[8,62,104],"masking":[9,105],"using":[10],"synthetic":[11],"aperture":[12],"radar":[13],"(SAR)":[14],"images,":[15],"which":[16,63],"is":[17,34,121,134],"based":[18],"on":[19,145],"level":[20,31],"set":[21,32],"method":[22,33,116],"and":[23,61,112,123,140],"fully":[24],"convolutional":[25],"network":[26],"(FCN)":[27],"classification.":[28],"First,":[29],"the":[30,37,53,66,80,87,92],"applied":[35],"cropped":[38],"SAR":[39,131,147],"input":[40,54],"image":[41,55],"for":[42,126],"initial":[43],"contours.":[44],"Second,":[45],"FCN":[46],"model":[47],"has":[48],"been":[49],"trained":[50],"classify":[52],"by":[56],"two":[57],"labels":[58],"of":[59,74,99,152],"water":[60],"will":[64],"find":[65],"possible":[67],"region":[68,73],"existing":[69],"real":[70],"coastlines,":[71],"named":[72],"interest":[75],"(RIO).":[76],"Third,":[77],"select":[79],"desired":[81],"contour":[82],"from":[83],"extracted":[84],"boundaries":[85],"in":[86,97,118,129],"first":[88],"step,":[89],"according":[90],"proportions":[93],"be":[95,107],"covered":[96],"RIO":[98],"step":[100],"two.":[101],"Then,":[102],"final":[103],"can":[106],"obtained":[108],"after":[109],"morphological":[110],"processing":[111],"color":[113],"filling.":[114],"The":[115],"proposed":[117],"this":[119,153],"fast":[122],"accurate":[124],"enough":[125],"ship":[127],"detection":[128],"high-resolution":[130],"images.":[132],"It":[133],"also":[135],"robust":[136],"speckle":[138],"noise":[139],"geographical":[141],"changes.":[142],"Experimental":[143],"results":[144],"GF-3":[146],"images":[148],"show":[149],"good":[150],"performance":[151],"method.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}