{"id":"https://openalex.org/W4294672813","doi":"https://doi.org/10.1109/rcar54675.2022.9872204","title":"A Lightweight Serial CNN Model for Remote Sensing Ship Target Recognition on FPGA","display_name":"A Lightweight Serial CNN Model for Remote Sensing Ship Target Recognition on FPGA","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4294672813","doi":"https://doi.org/10.1109/rcar54675.2022.9872204"},"language":"en","primary_location":{"id":"doi:10.1109/rcar54675.2022.9872204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rcar54675.2022.9872204","pdf_url":null,"source":{"id":"https://openalex.org/S4363608312","display_name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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/A5085763331","display_name":"Changyi Wang","orcid":"https://orcid.org/0000-0003-3153-9458"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Changyi Wang","raw_affiliation_strings":["Harbin Institute of Technology,School of Electronics and Information Engineering,Harbin,China,150080"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,School of Electronics and Information Engineering,Harbin,China,150080","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083989346","display_name":"Bowen Yao","orcid":"https://orcid.org/0000-0002-4719-9278"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Yao","raw_affiliation_strings":["Harbin Institute of Technology,School of Electronics and Information Engineering,Harbin,China,150080"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,School of Electronics and Information Engineering,Harbin,China,150080","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054381440","display_name":"Liansheng Liu","orcid":"https://orcid.org/0000-0001-5834-9772"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liansheng Liu","raw_affiliation_strings":["Harbin Institute of Technology,School of Electronics and Information Engineering,Harbin,China,150080"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,School of Electronics and Information Engineering,Harbin,China,150080","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101569648","display_name":"Peng Yu","orcid":"https://orcid.org/0000-0001-9908-2349"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Peng","raw_affiliation_strings":["Harbin Institute of Technology,School of Electronics and Information Engineering,Harbin,China,150080"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,School of Electronics and Information Engineering,Harbin,China,150080","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5085763331"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.1199,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.40760017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"14","issue":null,"first_page":"390","last_page":"395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9943000078201294,"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":0.9943000078201294,"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":0.9897000193595886,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.984499990940094,"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":0.7947633862495422},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6470301747322083},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6264255046844482},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5532613396644592},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.4588381350040436},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4472697973251343},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43331629037857056},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43187081813812256},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4292840361595154},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3906692564487457},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38692498207092285},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.35680750012397766},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.18834787607192993},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11350324749946594}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7947633862495422},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6470301747322083},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6264255046844482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5532613396644592},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.4588381350040436},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4472697973251343},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43331629037857056},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43187081813812256},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4292840361595154},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3906692564487457},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38692498207092285},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.35680750012397766},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.18834787607192993},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11350324749946594},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rcar54675.2022.9872204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rcar54675.2022.9872204","pdf_url":null,"source":{"id":"https://openalex.org/S4363608312","display_name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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":15,"referenced_works":["https://openalex.org/W2382910514","https://openalex.org/W2389492915","https://openalex.org/W2390366822","https://openalex.org/W2538041617","https://openalex.org/W2594177559","https://openalex.org/W2931948385","https://openalex.org/W2982083293","https://openalex.org/W2983807773","https://openalex.org/W3003656184","https://openalex.org/W3013723079","https://openalex.org/W3093308587","https://openalex.org/W3207453842","https://openalex.org/W4287119395","https://openalex.org/W6840454503","https://openalex.org/W7037928507"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W2355315220","https://openalex.org/W4200391368","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W2964954556","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Ship":[0],"target":[1],"recognition":[2,15,60,121],"with":[3,81],"remote":[4],"sensing":[5],"is":[6,40,129,135,144],"an":[7],"important":[8],"task":[9],"for":[10,22],"earth":[11],"observation.":[12],"The":[13,62,174],"excessive":[14],"delay":[16],"may":[17],"render":[18],"the":[19,37,43,58,70,78,96,125,132,152,178],"results":[20],"meaningless":[21],"time-sensitive":[23],"targets":[24,165],"such":[25],"as":[26,168],"ships.":[27,100,173],"Therefore,":[28],"rapid":[29],"and":[30,66,108,171],"timely":[31],"analysis":[32],"of":[33,45,99,155],"image":[34,134],"data":[35],"on":[36,77,124],"space-borne":[38,79],"platform":[39,80],"required.":[41],"With":[42],"development":[44],"deep":[46],"learning,":[47],"Convolution":[48],"Neural":[49],"Network":[50],"(CNN)-based":[51],"methods":[52,72,93,103],"have":[53],"achieved":[54],"high":[55],"accuracy":[56],"in":[57,90,185],"ship":[59,120,164],"task.":[61],"huge":[63],"model":[64,85],"size":[65],"computational":[67],"complexity":[68],"make":[69],"CNN-based":[71],"difficult":[73],"to":[74,94,146],"be":[75],"deployed":[76],"limited":[82],"resources.":[83],"Hence,":[84],"compression":[86],"techniques":[87],"are":[88,157,166],"adopted":[89,145],"some":[91],"on-board":[92,186],"obtain":[95],"real-time":[97],"information":[98],"However,":[101],"these":[102],"can":[104],"only":[105],"locate":[106],"ships":[107,148,156,170],"cannot":[109],"give":[110],"specific":[111],"category":[112],"information.":[113],"To":[114],"address":[115],"this":[116],"problem,":[117],"a":[118,141,181],"lightweight":[119,142],"method":[122,179],"based":[123],"subgraph":[126],"cascade":[127],"classification":[128],"proposed.":[130],"Firstly,":[131],"entire":[133],"divided":[136],"into":[137],"small":[138],"subgraphs.":[139],"Secondly,":[140],"CNN":[143],"select":[147],"from":[149],"backgrounds.":[150],"Then,":[151],"accurate":[153],"coordinates":[154],"obtained":[158],"through":[159],"position":[160],"regression.":[161],"At":[162],"last,":[163],"classified":[167],"civil":[169],"other":[172],"experiments":[175],"show":[176],"that":[177],"has":[180],"promising":[182],"application":[183],"prospect":[184],"intelligent":[187],"processing.":[188]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}