{"id":"https://openalex.org/W4406310290","doi":"https://doi.org/10.1016/j.ijin.2025.01.001","title":"Infrared spectral imaging-based image recognition for motion detection","display_name":"Infrared spectral imaging-based image recognition for motion detection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4406310290","doi":"https://doi.org/10.1016/j.ijin.2025.01.001"},"language":"en","primary_location":{"id":"doi:10.1016/j.ijin.2025.01.001","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijin.2025.01.001","pdf_url":null,"source":{"id":"https://openalex.org/S4210202467","display_name":"International Journal of Intelligent Networks","issn_l":"2666-6030","issn":["2666-6030"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Networks","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.ijin.2025.01.001","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100355406","display_name":"Yong Li","orcid":"https://orcid.org/0000-0002-6521-5921"},"institutions":[{"id":"https://openalex.org/I4210127074","display_name":"Zhongshan Hospital","ror":"https://ror.org/032x22645","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210127074"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yong Li","raw_affiliation_strings":["School of Mechanical and Electronic Engineering, Zhongshan Polytechnic, Zhongshan, 528400, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Electronic Engineering, Zhongshan Polytechnic, Zhongshan, 528400, Guangdong, China","institution_ids":["https://openalex.org/I4210127074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100355406"],"corresponding_institution_ids":["https://openalex.org/I4210127074"],"apc_list":{"value":800,"currency":"USD","value_usd":800},"apc_paid":{"value":800,"currency":"USD","value_usd":800},"fwci":11.4519,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.97229356,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"14","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9943000078201294,"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":0.9943000078201294,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9836000204086304,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9832000136375427,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6568408012390137},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6408830285072327},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4885924458503723},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44110584259033203},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.422402024269104}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6568408012390137},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6408830285072327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4885924458503723},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44110584259033203},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.422402024269104}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.ijin.2025.01.001","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijin.2025.01.001","pdf_url":null,"source":{"id":"https://openalex.org/S4210202467","display_name":"International Journal of Intelligent Networks","issn_l":"2666-6030","issn":["2666-6030"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Networks","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:343bbcb62aac4573bb04dfafe8446635","is_oa":true,"landing_page_url":"https://doaj.org/article/343bbcb62aac4573bb04dfafe8446635","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal of Intelligent Networks, Vol 6, Iss , Pp 14-26 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.ijin.2025.01.001","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijin.2025.01.001","pdf_url":null,"source":{"id":"https://openalex.org/S4210202467","display_name":"International Journal of Intelligent Networks","issn_l":"2666-6030","issn":["2666-6030"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Networks","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W2895634443","https://openalex.org/W2979907752","https://openalex.org/W2999064203","https://openalex.org/W3000573525","https://openalex.org/W3008266576","https://openalex.org/W3025874154","https://openalex.org/W3034968068","https://openalex.org/W3081597052","https://openalex.org/W3087951217","https://openalex.org/W3092465256","https://openalex.org/W3097114238","https://openalex.org/W3118256512","https://openalex.org/W3131328026","https://openalex.org/W3137137727","https://openalex.org/W3142003323","https://openalex.org/W3196388050","https://openalex.org/W3202399241","https://openalex.org/W3207608711","https://openalex.org/W4200124560","https://openalex.org/W4200376558","https://openalex.org/W4205405967","https://openalex.org/W4206934890","https://openalex.org/W4220903450","https://openalex.org/W4224943580","https://openalex.org/W4256226496","https://openalex.org/W4281662596","https://openalex.org/W4307530424","https://openalex.org/W4310566861","https://openalex.org/W4310984811","https://openalex.org/W4311144846","https://openalex.org/W4362653066","https://openalex.org/W4379356523","https://openalex.org/W4381891538","https://openalex.org/W4387090571","https://openalex.org/W6728852899","https://openalex.org/W6777183712","https://openalex.org/W6782508446","https://openalex.org/W6787588533","https://openalex.org/W6805272975","https://openalex.org/W6807433268","https://openalex.org/W6853113988","https://openalex.org/W6854080201","https://openalex.org/W7058835013"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"The":[0,148,192],"current":[1],"infrared":[2,39,46,55,62,95,107,113,223,247],"imaging":[3,63],"recognition":[4,103,144,229,242],"methods":[5,70],"are":[6,18],"inadequate":[7],"for":[8,13,71,88,126,227,239],"real-time":[9],"performance":[10,245],"and":[11,30,65,77,119,161,169,189,243],"accuracy":[12,168],"moving":[14],"objects.":[15,32],"Furthermore,":[16],"they":[17],"subject":[19],"to":[20,27,92,138,178],"several":[21],"constraints,":[22],"which":[23],"makes":[24],"it":[25],"challenging":[26],"recognize":[28],"stationary":[29],"occluded":[31],"Experts":[33],"have":[34,85],"conducted":[35],"comprehensive":[36],"research":[37,100,182],"on":[38,101,106],"imaging,":[40,109],"including":[41],"the":[42,51,66,72,94,110,122,131,134,139,143,152,173,181,207,241],"development":[43],"of":[44,53,68,75,82,112,133,145,155,163,175,204,219,246],"contour-based":[45],"motion":[47,96,127,140,146,234],"video":[48],"image":[49,56,102,224,228],"acquisition,":[50],"introduction":[52],"novel":[54],"generation":[57],"models":[58],"that":[59,151],"align":[60],"with":[61,121,172,200,215],"principles,":[64],"formulation":[67],"innovative":[69],"joint":[73],"classification":[74],"spatial-spectral":[76],"hyper-spectral":[78],"images.":[79,176],"However,":[80],"none":[81],"these":[83],"advancements":[84],"been":[86],"implemented":[87],"enhancement.":[89],"In":[90],"order":[91],"improve":[93],"target":[97,128],"detection":[98,141,170,244,248],"technology,":[99],"technology":[104],"based":[105],"spectral":[108],"establishment":[111],"radiation":[114],"characteristics":[115],"model":[116],"converted":[117],"image,":[118],"combined":[120],"local":[123,156],"binary":[124,157],"mode":[125],"feature":[129,159,164,225],"extraction,":[130],"construction":[132],"background":[135],"model,":[136],"applied":[137],"in":[142,167,233],"targets.":[147],"results":[149],"demonstrated":[150,184],"combination":[153],"effect":[154],"pattern":[158],"extraction":[160],"analysis":[162],"vectors":[165,226],"increased":[166],"rate":[171],"number":[174],"Compared":[177],"other":[179],"algorithms,":[180],"algorithm":[183],"a":[185,201,216],"superior":[186],"signal-to-noise":[187,196,211],"ratio":[188,197,212],"gain":[190,202,217],"amplitude.":[191],"unmanned":[193],"aerial":[194],"vehicle":[195],"was":[198,213],"13.487,":[199],"amplitude":[203,218],"2.214,":[205],"while":[206],"civil":[208],"aviation":[209],"aircraft":[210],"6.369,":[214],"1.792.":[220],"Therefore,":[221],"using":[222],"is":[230],"more":[231],"effective":[232],"detection,":[235],"providing":[236],"valuable":[237],"insights":[238],"improving":[240],"technology.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2025-10-10T00:00:00"}
