{"id":"https://openalex.org/W3016221231","doi":"https://doi.org/10.1109/icassp40776.2020.9054489","title":"A Novel Saliency-Driven Oil Tank Detection Method for Synthetic Aperture Radar Images","display_name":"A Novel Saliency-Driven Oil Tank Detection Method for Synthetic Aperture Radar Images","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3016221231","doi":"https://doi.org/10.1109/icassp40776.2020.9054489","mag":"3016221231"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5087779583","display_name":"Libao Zhang","orcid":"https://orcid.org/0000-0002-0888-2330"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Libao Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102848466","display_name":"Congyang Liu","orcid":"https://orcid.org/0009-0004-9431-4445"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Congyang Liu","raw_affiliation_strings":["School of Artificial Intelligence, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087779583"],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":0.5862,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.68090005,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2608","last_page":"2612"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9995999932289124,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9995999932289124,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9984999895095825,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9972000122070312,"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":0.8041295409202576},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.795346736907959},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6818740367889404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6657160520553589},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.6347507238388062},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.5958272218704224},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5444042682647705},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.5298516750335693},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46518152952194214},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.45988404750823975},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.44518160820007324},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.442608505487442},{"id":"https://openalex.org/keywords/azimuth","display_name":"Azimuth","score":0.4351557493209839},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4224841594696045},{"id":"https://openalex.org/keywords/inverse-synthetic-aperture-radar","display_name":"Inverse synthetic aperture radar","score":0.4145638942718506},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3246689438819885},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.2461698353290558},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.179592102766037}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.8041295409202576},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.795346736907959},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6818740367889404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6657160520553589},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.6347507238388062},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.5958272218704224},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5444042682647705},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.5298516750335693},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46518152952194214},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.45988404750823975},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44518160820007324},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.442608505487442},{"id":"https://openalex.org/C159737794","wikidata":"https://www.wikidata.org/wiki/Q124274","display_name":"Azimuth","level":2,"score":0.4351557493209839},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4224841594696045},{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.4145638942718506},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3246689438819885},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.2461698353290558},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.179592102766037},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/icassp40776.2020.9054489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W198035414","https://openalex.org/W787577717","https://openalex.org/W1602107991","https://openalex.org/W1963816830","https://openalex.org/W1978904636","https://openalex.org/W1981228217","https://openalex.org/W1990690548","https://openalex.org/W1999201441","https://openalex.org/W2002631607","https://openalex.org/W2025808729","https://openalex.org/W2088167233","https://openalex.org/W2105122499","https://openalex.org/W2116040950","https://openalex.org/W2128272608","https://openalex.org/W2131095668","https://openalex.org/W2140753134","https://openalex.org/W2148237766","https://openalex.org/W2162633365","https://openalex.org/W2292304773","https://openalex.org/W2337613213","https://openalex.org/W2384128575","https://openalex.org/W2746837200","https://openalex.org/W2748698787","https://openalex.org/W2760582944","https://openalex.org/W6682160523"],"related_works":["https://openalex.org/W2065648684","https://openalex.org/W2113052720","https://openalex.org/W2799624451","https://openalex.org/W2009383287","https://openalex.org/W2042914788","https://openalex.org/W2182190754","https://openalex.org/W4321264664","https://openalex.org/W2055824452","https://openalex.org/W2121688719","https://openalex.org/W2016481886"],"abstract_inverted_index":{"Synthetic":[0],"Aperture":[1],"Radar":[2],"(SAR)":[3],"imaging":[4],"system":[5],"plays":[6],"an":[7],"important":[8],"role":[9],"in":[10,22,56,158],"earth":[11],"observation":[12],"research.":[13],"This":[14],"leads":[15],"to":[16,49,73,99,120],"the":[17,44,57,62,68,81,86,101,107,110,115,130,133,140,145,151,155],"significance":[18],"of":[19,59,95,124,126,132],"target":[20],"detection":[21,35],"SAR":[23,39,54],"image.":[24],"In":[25],"this":[26],"paper,":[27],"we":[28,42],"propose":[29],"a":[30],"novel":[31],"saliency-driven":[32],"oil":[33,127,134],"tank":[34],"method":[36],"(SDD)":[37],"for":[38],"images.":[40],"First,":[41],"use":[43],"enhanced":[45],"directional":[46],"smoothing":[47],"(EDS)":[48],"remove":[50],"speckle":[51],"noise":[52],"from":[53,91],"images;":[55],"step":[58],"saliency":[60,103,108],"analysis,":[61],"integer":[63],"wavelet":[64],"transforms":[65],"(IWT)":[66],"and":[67,76,85,129,162],"DoG":[69],"filter":[70],"are":[71,97],"used":[72],"obtain":[74],"orientation":[75,82],"intensity":[77,87],"features,":[78],"respectively.":[79],"Then,":[80],"feature":[83,88],"map":[84,89],"resulting":[90],"these":[92],"two":[93],"kinds":[94],"features":[96],"utilized":[98],"compute":[100],"final":[102],"map;":[104],"after":[105],"segmenting":[106],"map,":[109],"obtained":[111],"connected":[112],"domain":[113],"guide":[114],"Active":[116],"Contour":[117],"Model":[118],"(ACM)":[119],"acquire":[121],"accurate":[122,163],"contours":[123],"tops":[125],"tanks,":[128],"bottoms":[131],"tanks":[135],"can":[136],"be":[137],"detected":[138],"by":[139],"strong":[141],"scattering":[142],"points":[143],"around":[144],"tops.":[146],"Experimental":[147],"results":[148],"show":[149],"that":[150],"proposed":[152],"model":[153],"outperforms":[154],"classical/state-of-the-art":[156],"models":[157],"maintaining":[159],"complete":[160],"targets":[161],"boundaries.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
