{"id":"https://openalex.org/W4286364677","doi":"https://doi.org/10.1109/lgrs.2022.3192559","title":"Multifeature Transformation and Fusion-Based Ship Detection With Small Targets and Complex Backgrounds","display_name":"Multifeature Transformation and Fusion-Based Ship Detection With Small Targets and Complex Backgrounds","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4286364677","doi":"https://doi.org/10.1109/lgrs.2022.3192559"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2022.3192559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3192559","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5045621730","display_name":"Mingfeng Zha","orcid":"https://orcid.org/0000-0003-0186-2940"},"institutions":[{"id":"https://openalex.org/I74837319","display_name":"Jiangxi Agricultural University","ror":"https://ror.org/00dc7s858","country_code":"CN","type":"education","lineage":["https://openalex.org/I74837319"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingfeng Zha","raw_affiliation_strings":["School of Software, Jiangxi Agricultural University, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0003-0186-2940","affiliations":[{"raw_affiliation_string":"School of Software, Jiangxi Agricultural University, Nanchang, China","institution_ids":["https://openalex.org/I74837319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101678567","display_name":"Wenbin Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I74837319","display_name":"Jiangxi Agricultural University","ror":"https://ror.org/00dc7s858","country_code":"CN","type":"education","lineage":["https://openalex.org/I74837319"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbin Qian","raw_affiliation_strings":["School of Software, Jiangxi Agricultural University, Nanchang, China"],"raw_orcid":"https://orcid.org/0000-0003-4108-9737","affiliations":[{"raw_affiliation_string":"School of Software, Jiangxi Agricultural University, Nanchang, China","institution_ids":["https://openalex.org/I74837319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101508597","display_name":"Wenji Yang","orcid":"https://orcid.org/0000-0003-3913-7437"},"institutions":[{"id":"https://openalex.org/I74837319","display_name":"Jiangxi Agricultural University","ror":"https://ror.org/00dc7s858","country_code":"CN","type":"education","lineage":["https://openalex.org/I74837319"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenji Yang","raw_affiliation_strings":["School of Software, Jiangxi Agricultural University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Jiangxi Agricultural University, Nanchang, China","institution_ids":["https://openalex.org/I74837319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016899209","display_name":"Yilu Xu","orcid":"https://orcid.org/0000-0003-2468-3443"},"institutions":[{"id":"https://openalex.org/I74837319","display_name":"Jiangxi Agricultural University","ror":"https://ror.org/00dc7s858","country_code":"CN","type":"education","lineage":["https://openalex.org/I74837319"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilu Xu","raw_affiliation_strings":["School of Software, Jiangxi Agricultural University, Nanchang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Jiangxi Agricultural University, Nanchang, China","institution_ids":["https://openalex.org/I74837319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5045621730"],"corresponding_institution_ids":["https://openalex.org/I74837319"],"apc_list":null,"apc_paid":null,"fwci":20.3984,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.99073327,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9976000189781189,"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"}},"topics":[{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9976000189781189,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12549","display_name":"Image and Object Detection Techniques","score":0.9729999899864197,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.6869634389877319},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5692244172096252},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5689809322357178},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3850458264350891},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38114580512046814},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3262982964515686},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.20007309317588806}],"concepts":[{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.6869634389877319},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5692244172096252},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5689809322357178},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3850458264350891},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38114580512046814},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3262982964515686},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.20007309317588806},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/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/lgrs.2022.3192559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3192559","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1813581380","display_name":null,"funder_award_id":"62166020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3773033885","display_name":null,"funder_award_id":"61966016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8679850373","display_name":null,"funder_award_id":"2020YFD1100605","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2570343428","https://openalex.org/W2752782242","https://openalex.org/W2774244034","https://openalex.org/W2884585870","https://openalex.org/W2898947732","https://openalex.org/W2928007866","https://openalex.org/W2934198733","https://openalex.org/W2962721361","https://openalex.org/W2963179609","https://openalex.org/W2963351448","https://openalex.org/W2964241181","https://openalex.org/W2982770724","https://openalex.org/W2986357608","https://openalex.org/W2991089415","https://openalex.org/W3018757597","https://openalex.org/W3034971973","https://openalex.org/W3035396860","https://openalex.org/W3038948729","https://openalex.org/W3041525128","https://openalex.org/W3101476123","https://openalex.org/W3107867277","https://openalex.org/W3120129399","https://openalex.org/W3160694286","https://openalex.org/W3172087149","https://openalex.org/W3197704289","https://openalex.org/W3198862447","https://openalex.org/W4214515471","https://openalex.org/W4293584584","https://openalex.org/W6750227808","https://openalex.org/W6771062828","https://openalex.org/W6777046832"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"With":[0],"the":[1,15,75,80,87,92,99,106,111,118,136,141,161,185,194,199,210,216,239],"development":[2],"of":[3,82,89,140,193,201,238],"deep":[4],"learning,":[5],"synthetic":[6],"aperture":[7],"radar":[8],"(SAR)":[9],"image":[10],"ship":[11,48,61,223],"detection":[12,32,51,62,224],"based":[13,65,97],"on":[14,66,98,221],"convolutional":[16,138,170],"neural":[17],"network":[18,143,155,195],"has":[19],"made":[20],"significant":[21],"progress.":[22],"However,":[23],"there":[24],"are":[25,182],"two":[26,187,191],"problems.":[27],"1)":[28],"The":[29,205],"false":[30],"alarm":[31],"rate":[33],"is":[34,52,71,102,115,132,156,213],"high":[35,119],"due":[36],"to":[37,54,73,78,104,117,134,144,197,215],"complex":[38],"background":[39],"and":[40,69,86,164,175,177,189,232,243],"coherent":[41],"speckle":[42],"noise":[43],"interference.":[44],"2)":[45],"For":[46],"smaller":[47],"targets,":[49],"missed":[50],"prone":[53],"occur.":[55],"In":[56,167],"this":[57],"letter,":[58],"a":[59,123,150],"novel":[60],"model":[63],"(MFTF-Net)":[64],"multi-feature":[67],"transformation":[68],"fusion":[70,154],"proposed":[72,211],"address":[74],"issues.":[76],"First,":[77],"avoid":[79],"randomness":[81],"initial":[83],"point":[84],"selection":[85],"influence":[88],"outlier":[90],"points,":[91],"anchor":[93],"frame":[94],"clustering":[95],"approach":[96],"K-medians++":[100],"algorithm":[101],"presented":[103],"cluster":[105],"object":[107],"candidate":[108],"frames.":[109],"Second,":[110],"low-level":[112],"feature":[113,153],"information":[114],"passed":[116],"level":[120],"by":[121],"constructing":[122],"local":[124],"enhancement":[125],"network;":[126],"then,":[127],"an":[128],"improved":[129,169],"Transformer":[130],"structure":[131],"introduced":[133],"replace":[135],"last":[137],"block":[139,171],"backbone":[142],"obtain":[145],"rich":[146],"contextual":[147],"information.":[148,166],"Finally,":[149],"four-scale":[151],"residual":[152],"designed,":[157],"which":[158],"fully":[159],"fuses":[160],"object’s":[162],"detailed":[163],"semantic":[165],"addition,":[168],"attention":[172,180],"module":[173],"(CBAM)":[174],"squeeze":[176],"excitation":[178],"(SE)":[179],"mechanisms":[181],"applied":[183],"in":[184,236],"lower":[186],"layers":[188,192],"upper":[190],"output":[196],"reduce":[198],"interference":[200],"confusing":[202],"information,":[203],"respectively.":[204],"experimental":[206],"results":[207],"demonstrate":[208],"that":[209],"method":[212],"superior":[214],"state-of-the-art":[217],"thirteen":[218],"baseline":[219],"models":[220],"SAR":[222,228],"dataset":[225,230],"(SSDD),":[226],"high-resolution":[227],"images":[229],"(HRSID),":[231],"SAR-ship-dataset":[233],"public":[234],"datasets":[235],"terms":[237],"mAP,":[240],"recall,":[241],"accuracy,":[242],"F1":[244],"metrics.":[245]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}