{"id":"https://openalex.org/W2911335464","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633118","title":"Hyperspectral Anomaly Dectection on Multicore DSPs","display_name":"Hyperspectral Anomaly Dectection on Multicore DSPs","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2911335464","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633118","mag":"2911335464"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2018.8633118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633118","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5102990451","display_name":"Yuan Li","orcid":"https://orcid.org/0000-0003-2747-5287"},"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":true,"raw_author_name":"Yuan Li","raw_affiliation_strings":["College of Information Science & Technology, Beijing University of Chemical Technology"],"affiliations":[{"raw_affiliation_string":"College of Information Science & Technology, Beijing University of Chemical Technology","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 & Technology, Beijing University of Chemical Technology"],"affiliations":[{"raw_affiliation_string":"College of Information Science & Technology, Beijing University of Chemical Technology","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100386304","display_name":"Lu Li","orcid":"https://orcid.org/0000-0001-9823-0565"},"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":"Lu Li","raw_affiliation_strings":["College of Information Science & Technology, Beijing University of Chemical Technology"],"affiliations":[{"raw_affiliation_string":"College of Information Science & Technology, Beijing University of Chemical Technology","institution_ids":["https://openalex.org/I75390827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102990451"],"corresponding_institution_ids":["https://openalex.org/I75390827"],"apc_list":null,"apc_paid":null,"fwci":0.2057,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61675776,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.972000002861023,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9668465852737427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7699205875396729},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.6086333394050598},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5818108320236206},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5074211955070496},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4849419891834259},{"id":"https://openalex.org/keywords/multi-core-processor","display_name":"Multi-core processor","score":0.47404003143310547},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.4733871519565582},{"id":"https://openalex.org/keywords/matlab","display_name":"MATLAB","score":0.45734333992004395},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3889545798301697},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35731762647628784},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.18157857656478882},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.17276501655578613}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9668465852737427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7699205875396729},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.6086333394050598},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5818108320236206},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5074211955070496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4849419891834259},{"id":"https://openalex.org/C78766204","wikidata":"https://www.wikidata.org/wiki/Q555032","display_name":"Multi-core processor","level":2,"score":0.47404003143310547},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.4733871519565582},{"id":"https://openalex.org/C2780365114","wikidata":"https://www.wikidata.org/wiki/Q169478","display_name":"MATLAB","level":2,"score":0.45734333992004395},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3889545798301697},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35731762647628784},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.18157857656478882},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.17276501655578613},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2018.8633118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633118","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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":9,"referenced_works":["https://openalex.org/W1965123331","https://openalex.org/W2002849025","https://openalex.org/W2012976027","https://openalex.org/W2014238333","https://openalex.org/W2022470997","https://openalex.org/W2116325143","https://openalex.org/W2131697388","https://openalex.org/W2142384244","https://openalex.org/W2156462339"],"related_works":["https://openalex.org/W2911259277","https://openalex.org/W4386427838","https://openalex.org/W2800956885","https://openalex.org/W2533019003","https://openalex.org/W1788560349","https://openalex.org/W2626158795","https://openalex.org/W2078656815","https://openalex.org/W2391021239","https://openalex.org/W2560525382","https://openalex.org/W2126575155"],"abstract_inverted_index":{"As":[0,58],"one":[1],"of":[2,22,32,76,85,134,168],"the":[3,15,17,30,36,74,96,103,109,132,143,147,166,169],"major":[4],"technological":[5],"breakthroughs":[6],"made":[7],"by":[8,50,127],"human":[9],"beings":[10],"in":[11,64,73,122,146],"earth":[12],"observation":[13,62],"since":[14],"1980s,":[16],"good":[18],"spectral":[19,53,120],"diagnostic":[20],"ability":[21],"hyperspectral":[23,104,110,155,160],"images":[24,47,105],"makes":[25],"it":[26],"very":[27],"suitable":[28],"for":[29,159],"discovery":[31],"artificial":[33],"targets":[34],"against":[35],"natural":[37],"background":[38,119],"and":[39,43,55,91,176,188],"therefore":[40],"receives":[41],"more":[42,44,65],"attention.":[45],"Hyperspectral":[46],"are":[48],"characterized":[49],"their":[51],"high":[52],"resolution":[54],"large":[56],"band.":[57],"they":[59,67],"provide":[60],"detailed":[61],"information":[63,121],"fields,":[66],"also":[68],"bring":[69],"about":[70,81],"an":[71],"increase":[72],"amount":[75],"data":[77],"redundancy,":[78],"which":[79],"brings":[80],"a":[82],"great":[83],"deal":[84],"difficulty":[86],"corresponding":[87],"transmission,":[88],"storage,":[89],"processing":[90],"application.":[92],"In":[93],"this":[94],"paper,":[95],"multi-core":[97,135],"DSP":[98,136,180],"is":[99,112,125,157],"applied":[100,158],"to":[101,164],"realize":[102,142],"anomaly":[106,162],"detection.":[107],"Firstly,":[108],"image":[111,161],"split":[113],"into":[114],"several":[115],"blocks.":[116],"And":[117],"then":[118],"each":[123],"blocks":[124],"extracted":[126],"Sherman-Morrison":[128],"formula":[129],"sequentially.":[130],"Finally,":[131],"parallelization":[133],"with":[137,149,174],"high-speed":[138],"computing":[139],"performance":[140,187],"can":[141],"realtime":[144],"required":[145],"application":[148],"RX":[150],"detection":[151,163,182,186],"algorithm.":[152],"The":[153],"real":[154],"dataset":[156],"verify":[165],"validity":[167],"proposed":[170],"method.":[171],"Furthermore,":[172],"comparing":[173],"MATLAB":[175],"CPU":[177],"experimental":[178],"results,":[179],"parallel":[181],"system":[183],"has":[184],"better":[185],"high-efficient.":[189]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}