{"id":"https://openalex.org/W4390871481","doi":"https://doi.org/10.1109/lgrs.2024.3354282","title":"A Compact and High-Efficiency Anchor-Free Network Based on Contour Key Points for SAR Ship Detection","display_name":"A Compact and High-Efficiency Anchor-Free Network Based on Contour Key Points for SAR Ship Detection","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4390871481","doi":"https://doi.org/10.1109/lgrs.2024.3354282"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2024.3354282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2024.3354282","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/A5005815194","display_name":"Fei Gao","orcid":"https://orcid.org/0000-0002-0359-1155"},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Gao","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Yangtze University, Jingzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0359-1155","affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Yangtze University, Jingzhou, China","institution_ids":["https://openalex.org/I177739611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101656884","display_name":"Changxin Cai","orcid":"https://orcid.org/0000-0002-3525-6773"},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changxin Cai","raw_affiliation_strings":["School of Electronic Information and Electrical Engineering, Yangtze University, Jingzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3525-6773","affiliations":[{"raw_affiliation_string":"School of Electronic Information and Electrical Engineering, Yangtze University, Jingzhou, China","institution_ids":["https://openalex.org/I177739611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101907120","display_name":"Wentao Tang","orcid":"https://orcid.org/0000-0003-0392-2580"},"institutions":[{"id":"https://openalex.org/I4210116247","display_name":"Jingchu University of Technology","ror":"https://ror.org/037kvhq82","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210116247"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wentao Tang","raw_affiliation_strings":["School of Electronic Information Engineering, Jingchu University of Technology, Jingmen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information Engineering, Jingchu University of Technology, Jingmen, China","institution_ids":["https://openalex.org/I4210116247"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080153028","display_name":"Yiming He","orcid":"https://orcid.org/0000-0001-5338-5889"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiming He","raw_affiliation_strings":["School of Electronic Information, Guangxi University, Nanning, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.6787,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.94099398,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"21","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.998199999332428,"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":0.998199999332428,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9890999794006348,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9810000061988831,"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":0.7852894067764282},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6899186372756958},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6384179592132568},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6289780139923096},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5847578048706055},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5698255300521851},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.5574785470962524},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4943368434906006},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45838186144828796},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4544321894645691},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4415639042854309},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.43345069885253906},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4326927661895752},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4281836748123169},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.280624657869339},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11935064196586609}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7852894067764282},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6899186372756958},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6384179592132568},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6289780139923096},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5847578048706055},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5698255300521851},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.5574785470962524},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4943368434906006},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45838186144828796},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4544321894645691},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4415639042854309},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.43345069885253906},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4326927661895752},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4281836748123169},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.280624657869339},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11935064196586609},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2024.3354282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2024.3354282","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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2194775991","https://openalex.org/W2907034392","https://openalex.org/W2934198733","https://openalex.org/W2947256382","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2986357608","https://openalex.org/W2989604896","https://openalex.org/W3012573144","https://openalex.org/W3038948729","https://openalex.org/W3041525128","https://openalex.org/W3184439416","https://openalex.org/W3200733355","https://openalex.org/W4323338302","https://openalex.org/W4367665802","https://openalex.org/W6780959388","https://openalex.org/W6798838024"],"related_works":["https://openalex.org/W143502885","https://openalex.org/W42113618","https://openalex.org/W2103468410","https://openalex.org/W2480115405","https://openalex.org/W3197542402","https://openalex.org/W1856228368","https://openalex.org/W2971527398","https://openalex.org/W82829784","https://openalex.org/W4361003569","https://openalex.org/W2981421796"],"abstract_inverted_index":{"As":[0],"computer":[1],"vision":[2],"advances,":[3],"synthetic":[4],"aperture":[5],"radar":[6],"(SAR)":[7],"ship":[8,50,98,168],"detection":[9,169],"increasingly":[10],"incorporates":[11],"deep":[12],"learning":[13],"techniques":[14],"based":[15],"on":[16,26],"convolutional":[17],"neural":[18],"networks":[19,37],"(CNNs).":[20],"Presently,":[21],"these":[22],"approaches":[23],"predominantly":[24],"depend":[25],"large":[27],"network":[28,57,78,193],"architectures":[29],"and":[30,71,96,120,140,149,172,189,207,215],"anchor-based":[31,106],"object":[32,84,117,123],"representation":[33,85],"methods.":[34],"Although":[35],"such":[36],"can":[38],"yield":[39],"superior":[40],"results,":[41],"they":[42],"are":[43],"often":[44],"inefficient":[45],"in":[46,87],"detection.":[47],"For":[48],"SAR":[49,167,174],"detection,":[51],"this":[52,109,218],"letter":[53],"proposes":[54],"a":[55,67,113,156],"novel":[56],"structure,":[58],"the":[59,101,127,166,212],"Contour":[60,81],"Key":[61,82],"Points":[62,83],"Network":[63],"(CPoints-Net),":[64],"which":[65],"utilizes":[66],"compact":[68],"backbone":[69],"ResNet18":[70],"Feature":[72],"Pyramid":[73],"Structure":[74],"(FPN)":[75],"to":[76,146,154,163],"enhance":[77],"efficiency.":[79],"The":[80],"employed":[86],"CPoints-Net":[88,133,178],"is":[89,223],"an":[90],"anchor-free":[91,110],"method":[92],"that":[93],"directly":[94],"locates":[95],"represents":[97],"objects,":[99],"circumventing":[100],"complex":[102],"post-processing":[103],"associated":[104],"with":[105,198],"techniques.":[107],"Furthermore,":[108],"approach":[111],"preserves":[112],"higher":[114],"degree":[115],"of":[116,129,160,187,204,217],"feature":[118,136,142],"information,":[119],"enables":[121],"direct":[122],"prediction.":[124],"To":[125],"address":[126],"distribution":[128],"contour":[130],"key":[131,161],"points,":[132],"applies":[134],"pointwise":[135],"grouping":[137,143],"(PFG)":[138],"part":[139,145],"dynamic":[141],"(DyFG)":[144],"refine":[147],"features":[148],"employs":[150],"Deformable":[151],"Convolution":[152],"(DCN)":[153],"achieve":[155],"more":[157],"precise":[158],"fit":[159],"points":[162],"contours.":[164],"On":[165],"dataset":[170,176],"(SSDD)":[171],"high-resolution":[173],"images":[175],"(HRSID),":[177],"achieves":[179],"<italic":[180],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[181,184],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">AP</i>":[182],"<sub":[183],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">50</sub>":[185],"scores":[186],"96.3%":[188],"90.5%,":[190],"respectively.":[191],"This":[192],"has":[194],"18.64M":[195],"parameters":[196],"(Params),":[197],"Frames":[199],"Per":[200],"Second":[201],"(FPS)":[202],"rates":[203],"43.8":[205],"img/s":[206,209],"32.6":[208],"respectively,":[210],"demonstrating":[211],"optimal":[213],"performance":[214],"efficiency":[216],"network.":[219],"Its":[220],"source":[221],"code":[222],"located":[224],"at":[225],"https://github.com/Daniel-tech307/CPoints_net.git.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}