{"id":"https://openalex.org/W2734407021","doi":"https://doi.org/10.1109/icaci.2017.7974476","title":"Inland ship detection based on dynamic group sparsity","display_name":"Inland ship detection based on dynamic group sparsity","publication_year":2017,"publication_date":"2017-02-01","ids":{"openalex":"https://openalex.org/W2734407021","doi":"https://doi.org/10.1109/icaci.2017.7974476","mag":"2734407021"},"language":"en","primary_location":{"id":"doi:10.1109/icaci.2017.7974476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaci.2017.7974476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Ninth International Conference on Advanced Computational Intelligence (ICACI)","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/A5109387304","display_name":"Langqi Mei","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Langqi Mei","raw_affiliation_strings":["School of Automation, Wuhan University of Technology, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002890728","display_name":"Jianming Guo","orcid":"https://orcid.org/0000-0002-7012-9542"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianming Guo","raw_affiliation_strings":["School of Automation, Wuhan University of Technology, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070739275","display_name":"Pingping Lu","orcid":"https://orcid.org/0000-0003-1486-7580"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pingping Lu","raw_affiliation_strings":["School of Automation, Wuhan University of Technology, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100345153","display_name":"Qing Liu","orcid":"https://orcid.org/0000-0001-5286-4423"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Liu","raw_affiliation_strings":["School of Automation, Wuhan University of Technology, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071883673","display_name":"Teng Fei","orcid":"https://orcid.org/0000-0002-3415-1654"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Teng","raw_affiliation_strings":["School of Energy and Power Engineering, Wuhan University of Technology, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Energy and Power Engineering, Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.7856,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.97793669,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9976999759674072,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9944000244140625,"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/group","display_name":"Group (periodic table)","score":0.6316401958465576},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5861011743545532}],"concepts":[{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.6316401958465576},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5861011743545532},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaci.2017.7974476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaci.2017.7974476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Ninth International Conference on Advanced Computational Intelligence (ICACI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1608074891","https://openalex.org/W1994634851","https://openalex.org/W2028629089","https://openalex.org/W2031758356","https://openalex.org/W2052524720","https://openalex.org/W2102625004","https://openalex.org/W2114701396","https://openalex.org/W2121735136","https://openalex.org/W2127070222","https://openalex.org/W2127271355","https://openalex.org/W2140235142","https://openalex.org/W2145096794","https://openalex.org/W2149027517","https://openalex.org/W2158604775","https://openalex.org/W2160979406","https://openalex.org/W2289917018","https://openalex.org/W2522686865","https://openalex.org/W2538773003","https://openalex.org/W3003662786","https://openalex.org/W4250955649","https://openalex.org/W6678295550","https://openalex.org/W6728784960"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"Effective":[0],"and":[1,22,52,58,114],"efficient":[2],"ship":[3,17,27,38],"detection":[4,39,105],"is":[5,43,46,76,89,100],"a":[6,35,90,135],"prerequisite":[7],"in":[8,78,111,117],"inland":[9,37],"video":[10],"surveillance,":[11],"e.g.":[12],"to":[13,20,23,28],"track":[14],"the":[15,25,82,94,118,139],"target":[16],"from":[18],"frame":[19,21,88],"analyze":[24],"tracked":[26],"recognize":[29],"its":[30],"behavior.":[31],"In":[32],"this":[33],"paper,":[34],"real-time":[36],"algorithm":[40],"called":[41],"MEADGS":[42],"proposed,":[44],"which":[45],"based":[47,64],"on":[48,65],"dynamic":[49,68],"group":[50,69],"sparsity":[51,70],"background":[53,57,74,84],"subtraction":[54],"method.":[55],"The":[56,73,107,124],"foreground":[59],"image":[60,85],"are":[61,109],"reconstructed":[62],"directly":[63],"enhanced":[66],"adaptive":[67],"(EAdaDGS)":[71],"algorithm.":[72],"dictionary":[75],"updated":[77],"real":[79],"time":[80],"by":[81,103],"current":[83,87],"when":[86],"key":[91],"frame.":[92],"Meanwhile,":[93],"efficiency":[95],"of":[96,121],"our":[97,129],"proposed":[98,130],"method":[99,131,142],"further":[101],"improved":[102],"multi-resolution":[104],"procedure.":[106],"ships":[108],"located":[110],"low":[112],"resolution,":[113],"detected":[115],"accurately":[116],"specified":[119],"area":[120],"high":[122],"resolution.":[123],"experimental":[125],"results":[126],"show":[127],"that":[128],"obtains":[132],"higher-quality,":[133],"with":[134],"7.6%":[136],"margin":[137],"over":[138],"second":[140],"best":[141],"performance.":[143]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}