{"id":"https://openalex.org/W2902279324","doi":"https://doi.org/10.1109/icpr.2018.8546043","title":"Low-Rank and Sparse Decomposition on Contrast Map for Small Infrared Target Detection","display_name":"Low-Rank and Sparse Decomposition on Contrast Map for Small Infrared Target Detection","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902279324","doi":"https://doi.org/10.1109/icpr.2018.8546043","mag":"2902279324"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8546043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5103237796","display_name":"Xiaoya Deng","orcid":"https://orcid.org/0000-0002-2758-2579"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoya Deng","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100317994","display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-7015-7335"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100601086","display_name":"Liwei Li","orcid":"https://orcid.org/0000-0002-5125-7725"},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liwei Li","raw_affiliation_strings":["Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing, China","institution_ids":["https://openalex.org/I4210128053"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100454485","display_name":"Wenjuan Zhang","orcid":"https://orcid.org/0000-0002-0534-0974"},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjuan Zhang","raw_affiliation_strings":["Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing, China","institution_ids":["https://openalex.org/I4210128053"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445622","display_name":"Xia Li","orcid":"https://orcid.org/0000-0003-3050-8529"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia Li","raw_affiliation_strings":["Science and Technology on Optical Radiation Laboratory, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Optical Radiation Laboratory, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.5352,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.97790227,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"52","issue":null,"first_page":"2682","last_page":"2687"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9998999834060669,"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":0.9998999834060669,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.9944000244140625,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7128240466117859},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6529216170310974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.633074939250946},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6029541492462158},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.5325151085853577},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5261494517326355},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5170379281044006},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5050662159919739},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.5023367404937744},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4569327235221863},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4497430920600891},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4406965672969818},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4108119010925293},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.37144675850868225},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1915505826473236}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7128240466117859},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6529216170310974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.633074939250946},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6029541492462158},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.5325151085853577},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5261494517326355},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5170379281044006},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5050662159919739},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.5023367404937744},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4569327235221863},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4497430920600891},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4406965672969818},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4108119010925293},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.37144675850868225},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1915505826473236},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8546043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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":18,"referenced_works":["https://openalex.org/W1974872009","https://openalex.org/W1978993121","https://openalex.org/W1992873714","https://openalex.org/W1994048688","https://openalex.org/W2016880985","https://openalex.org/W2028317119","https://openalex.org/W2041560658","https://openalex.org/W2041888557","https://openalex.org/W2067173181","https://openalex.org/W2118702465","https://openalex.org/W2139356527","https://openalex.org/W2142077116","https://openalex.org/W2291670705","https://openalex.org/W2341998679","https://openalex.org/W2540854551","https://openalex.org/W2547673833","https://openalex.org/W2604768956","https://openalex.org/W6681016373"],"related_works":["https://openalex.org/W2109115373","https://openalex.org/W2390901981","https://openalex.org/W2353818951","https://openalex.org/W1605879311","https://openalex.org/W2611980620","https://openalex.org/W4230691760","https://openalex.org/W2385763735","https://openalex.org/W4391923333","https://openalex.org/W2386394344","https://openalex.org/W3014558862"],"abstract_inverted_index":{"Small":[0],"infrared":[1],"target":[2,63],"detection":[3,12,29,64],"is":[4,39,66,76,86,107],"a":[5,79],"key":[6],"and":[7,13,71,90,110],"challenging":[8],"issue":[9],"in":[10],"object":[11],"tracking":[14],"systems.":[15],"Existing":[16],"algorithms":[17],"can":[18],"be":[19],"mainly":[20,40],"categorized":[21],"into":[22],"nonlocal-based":[23],"or":[24,53],"local-based":[25],"methods.":[26],"However,":[27],"the":[28,57,84,100,103,119],"performance":[30],"degrades":[31],"rapidly":[32],"when":[33],"facing":[34],"highly":[35],"heterogeneous":[36],"backgrounds.":[37],"This":[38],"due":[41],"to":[42,68],"that":[43],"they":[44],"exploit":[45],"only":[46],"one":[47],"kind":[48],"of":[49,102],"information":[50],"(e.g.,":[51],"local":[52,70],"nonlocal)":[54],"while":[55,83],"sacrificing":[56],"other.":[58],"Thus,":[59],"an":[60],"effective":[61],"small":[62],"method":[65],"proposed":[67,104],"combine":[69],"nonlocal":[72],"priors.":[73],"The":[74],"former":[75],"obtained":[77],"by":[78,88],"sliding":[80],"dual":[81],"window":[82],"latter":[85],"realized":[87],"low-rank":[89],"sparse":[91],"decomposition.":[92],"Experimental":[93],"results":[94],"on":[95],"three":[96],"real":[97],"datasets":[98],"validate":[99],"effectiveness":[101],"framework,":[105],"which":[106],"more":[108],"stable":[109],"robust":[111],"compared":[112],"with":[113,122],"several":[114],"state-of-the-art":[115],"methods,":[116],"especially":[117],"for":[118],"image":[120],"scenes":[121],"heavy":[123],"background":[124],"clutters.":[125]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}