{"id":"https://openalex.org/W4400489243","doi":"https://doi.org/10.1109/jstars.2024.3426288","title":"M-FSDistill: A Feature Map Knowledge Distillation Algorithm for SAR Ship Detection","display_name":"M-FSDistill: A Feature Map Knowledge Distillation Algorithm for SAR Ship Detection","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400489243","doi":"https://doi.org/10.1109/jstars.2024.3426288"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2024.3426288","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2024.3426288","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2024.3426288","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015569059","display_name":"Guohui Wang","orcid":"https://orcid.org/0009-0000-9094-3878"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]},{"id":"https://openalex.org/I2800393352","display_name":"China Tourism Academy","ror":"https://ror.org/01k4abj61","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800393352"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guohui Wang","raw_affiliation_strings":["Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, China","School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0000-9094-3878","affiliations":[{"raw_affiliation_string":"Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, China","institution_ids":["https://openalex.org/I2800393352"]},{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002364697","display_name":"Rui Qin","orcid":"https://orcid.org/0000-0003-1123-0090"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]},{"id":"https://openalex.org/I2800393352","display_name":"China Tourism Academy","ror":"https://ror.org/01k4abj61","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800393352"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Qin","raw_affiliation_strings":["Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, China","School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-1123-0090","affiliations":[{"raw_affiliation_string":"Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, China","institution_ids":["https://openalex.org/I2800393352"]},{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062996827","display_name":"Ying Xia","orcid":"https://orcid.org/0000-0002-7407-6126"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]},{"id":"https://openalex.org/I2800393352","display_name":"China Tourism Academy","ror":"https://ror.org/01k4abj61","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800393352"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Xia","raw_affiliation_strings":["Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, China","School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-7407-6126","affiliations":[{"raw_affiliation_string":"Key Laboratory of Tourism Multisource Data Perception and Decision, Ministry of Culture and Tourism, China","institution_ids":["https://openalex.org/I2800393352"]},{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":1.4306,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.82404126,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"17","issue":null,"first_page":"13217","last_page":"13231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"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":0.9975000023841858,"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":0.9922000169754028,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9886000156402588,"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/computer-science","display_name":"Computer science","score":0.7097271680831909},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.60572749376297},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5691112279891968},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46413251757621765},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46209612488746643},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43033671379089355},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.426291286945343},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3932769298553467},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.35434186458587646},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32669463753700256},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.130741685628891}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7097271680831909},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.60572749376297},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5691112279891968},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46413251757621765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46209612488746643},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43033671379089355},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.426291286945343},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3932769298553467},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.35434186458587646},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32669463753700256},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.130741685628891},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2024.3426288","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2024.3426288","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:89530feeeab44e2f9ad8e32546f271af","is_oa":true,"landing_page_url":"https://doaj.org/article/89530feeeab44e2f9ad8e32546f271af","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 13217-13231 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2024.3426288","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2024.3426288","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2102605133","https://openalex.org/W2747165560","https://openalex.org/W2750784772","https://openalex.org/W2772623520","https://openalex.org/W2904480641","https://openalex.org/W2964241181","https://openalex.org/W2970277117","https://openalex.org/W2982220924","https://openalex.org/W2986357608","https://openalex.org/W3035396860","https://openalex.org/W3038948729","https://openalex.org/W3107474049","https://openalex.org/W3112594048","https://openalex.org/W3116504381","https://openalex.org/W3200733355","https://openalex.org/W3207877247","https://openalex.org/W3208021485","https://openalex.org/W3214932270","https://openalex.org/W4205093529","https://openalex.org/W4213156196","https://openalex.org/W4213455178","https://openalex.org/W4214524539","https://openalex.org/W4214571488","https://openalex.org/W4225326762","https://openalex.org/W4284689887","https://openalex.org/W4285166851","https://openalex.org/W4285294301","https://openalex.org/W4288325606","https://openalex.org/W4293811989","https://openalex.org/W4313141028","https://openalex.org/W4322730913","https://openalex.org/W4360604925","https://openalex.org/W4381745299","https://openalex.org/W4385627575","https://openalex.org/W4386071462","https://openalex.org/W4386071817","https://openalex.org/W4388766903","https://openalex.org/W6620707391","https://openalex.org/W6743188669","https://openalex.org/W6764322716","https://openalex.org/W6789011712","https://openalex.org/W6839547478"],"related_works":["https://openalex.org/W3026162553","https://openalex.org/W2121524756","https://openalex.org/W2768175398","https://openalex.org/W782553550","https://openalex.org/W2344382886","https://openalex.org/W2355001665","https://openalex.org/W19111321","https://openalex.org/W2158111730","https://openalex.org/W2412887479","https://openalex.org/W4252699458"],"abstract_inverted_index":{"Limited":[0],"by":[1,156,264],"the":[2,13,63,72,87,104,142,151,163,194,197,226,241,262],"capacity":[3],"and":[4,18,45,89,111,126,159,174,188,209,216,247,258,267],"computing":[5],"ability":[6],"of":[7,15,20,65,68,75,108,114,153,184,196,255],"platform":[8],"payload,":[9],"researchers":[10],"often":[11],"face":[12],"challenge":[14],"balancing":[16],"lightness":[17],"performance":[19,67,106,195],"models":[21,31,227],"in":[22,53,86,117,136,234],"synthetic":[23],"aperture":[24],"radar":[25],"(SAR)":[26],"ship":[27,96,133,164,186,205],"detection,":[28],"especially":[29,93],"for":[30,94,131],"based":[32,249],"on":[33,203,240,250],"deep":[34],"learning.":[35],"Nonetheless,":[36],"traditional":[37],"lightweight":[38,69],"methods,":[39],"such":[40,82],"as":[41,83],"reduced":[42],"convolutional":[43],"layers":[44],"pruning,":[46],"can":[47],"easily":[48],"lead":[49],"to":[50,61,80,102,138,149,179],"missed":[51],"detections":[52,113],"models.":[54,70],"Researchers":[55],"have":[56],"introduced":[57],"knowledge":[58,155],"distillation":[59,91,109,118,129,140,145,154],"algorithms":[60,76,110],"address":[62,103],"issue":[64],"poor":[66],"However,":[71],"improvement":[73,107],"effect":[74],"is":[77,147],"limited":[78,105],"due":[79],"shortcomings":[81],"noise":[84],"interference":[85],"background":[88],"improper":[90],"strategies,":[92],"small":[95,115,185],"detection":[97,206],"with":[98,218],"complex":[99],"backgrounds.":[100],"Aiming":[101],"missing":[112,190],"ships":[116],"models,":[119],"we":[120,200],"propose":[121],"a":[122,170],"multiscale":[123,176],"feature":[124,128,143,165,171],"enhancement":[125,167],"foreground-scene":[127],"algorithm":[130,178,230],"SAR":[132,204,211],"detection.":[134,191],"Specifically,":[135],"order":[137],"improve":[139,150],"efficiency,":[141],"learning":[144,183],"module":[146,168],"proposed":[148,198],"quality":[152],"separating":[157],"foreground":[158],"scene":[160],"distillation.":[161],"Then,":[162],"representation":[166],"utilizes":[169],"map":[172],"decoupling":[173],"attention-based":[175],"fusion":[177],"enhance":[180],"student":[181],"model's":[182],"features":[187],"reduce":[189],"To":[192],"validate":[193],"method,":[199],"conducted":[201],"experiments":[202],"dataset":[207,213],"(SSDD)":[208],"high-resolution":[210],"images":[212],"(HRSID)":[214],"datasets":[215],"compared":[217],"several":[219],"advanced":[220],"methods.":[221],"The":[222],"results":[223],"indicate":[224],"that":[225],"using":[228],"our":[229],"achieved":[231,252],"significant":[232],"improvements":[233],"average":[235],"precision":[236],"(AP).":[237],"For":[238],"instance,":[239],"SSDD":[242],"dataset,":[243],"RetinaNet,":[244],"Cascade":[245],"R-CNN,":[246],"RepPoints":[248],"ResNet18":[251],"AP":[253],"scores":[254],"95.5%,":[256],"95.4%,":[257],"95.9%":[259],"respectively,":[260],"surpassing":[261],"baseline":[263],"3.9%,":[265],"3.1%,":[266],"1.9%.":[268]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
