{"id":"https://openalex.org/W7221454792","doi":"https://doi.org/10.11591/ijai.v15.i5.pp4946-4960","title":"Investigating the use of near infrared in household object recognition","display_name":"Investigating the use of near infrared in household object recognition","publication_year":2026,"publication_date":"2026-10-01","ids":{"openalex":"https://openalex.org/W7221454792","doi":"https://doi.org/10.11591/ijai.v15.i5.pp4946-4960"},"language":"en","primary_location":{"id":"doi:10.11591/ijai.v15.i5.pp4946-4960","doi":"https://doi.org/10.11591/ijai.v15.i5.pp4946-4960","is_oa":true,"landing_page_url":"https://doi.org/10.11591/ijai.v15.i5.pp4946-4960","pdf_url":"https://ijai.iaescore.com/index.php/IJAI/article/download/27714/15459","source":{"id":"https://openalex.org/S2764408626","display_name":"IAES International Journal of Artificial Intelligence","issn_l":"2089-4872","issn":["2089-4872","2252-8938"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315009","host_organization_name":"Institute of Advanced Engineering and Science (IAES)","host_organization_lineage":["https://openalex.org/P4310315009"],"host_organization_lineage_names":["Institute of Advanced Engineering and Science (IAES)"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IAES International Journal of Artificial Intelligence (IJ-AI)","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W7221454792"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ijai.iaescore.com/index.php/IJAI/article/download/27714/15459","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004190563","display_name":"Muhammad Attamimi","orcid":"https://orcid.org/0000-0002-0829-7748","observed_orcids":["https://orcid.org/0000-0002-0829-7748"]},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Institut Teknologi Sepuluh Nopember","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Muhammad Attamimi","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember"],"raw_orcid":"https://orcid.org/0000-0002-0829-7748","affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5158359358","display_name":"Muhammad Ammar Aiman Majid","orcid":"https://orcid.org/0009-0006-6202-6021","observed_orcids":["https://orcid.org/0009-0006-6202-6021"]},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Institut Teknologi Sepuluh Nopember","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Muhammad Ammar Aiman Majid","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember"],"raw_orcid":"https://orcid.org/0009-0006-6202-6021","affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108129766","display_name":"Hendra Kusuma","orcid":"https://orcid.org/0009-0003-5350-3250","observed_orcids":["https://orcid.org/0009-0003-5350-3250"]},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Institut Teknologi Sepuluh Nopember","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Hendra Kusuma","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember"],"raw_orcid":"https://orcid.org/0009-0003-5350-3250","affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008600046","display_name":"Muhammad Rivai","orcid":"https://orcid.org/0000-0002-3615-1658","observed_orcids":["https://orcid.org/0000-0002-3615-1658"]},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Institut Teknologi Sepuluh Nopember","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Muhammad Rivai","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember"],"raw_orcid":"https://orcid.org/0000-0002-3615-1658","affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034488154","display_name":"Rudy Dikairono","orcid":"https://orcid.org/0000-0001-7950-1366","observed_orcids":["https://orcid.org/0000-0001-7950-1366"]},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Institut Teknologi Sepuluh Nopember","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Rudy Dikairono","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember"],"raw_orcid":"https://orcid.org/0000-0001-7950-1366","affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember","institution_ids":["https://openalex.org/I166843116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I166843116"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":"5","first_page":"4946","last_page":"4946"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9442999958992004,"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":0.9442999958992004,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.011800000444054604,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.008899999782443047,"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/near-infrared-imaging","display_name":"near-infrared imaging","score":0.8259999752044678},{"id":"https://openalex.org/keywords/illumination-robustness","display_name":"illumination robustness","score":0.7730000019073486},{"id":"https://openalex.org/keywords/low-light-recognition","display_name":"low-light recognition","score":0.48899999260902405},{"id":"https://openalex.org/keywords/domestic-robots","display_name":"home robots","score":0.652999997138977},{"id":"https://openalex.org/keywords/efficientnet","display_name":"EfficientNet","score":0.531000018119812},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.8949999809265137},{"id":"https://openalex.org/keywords/multimodal-fusion","display_name":"multimodal fusion","score":0.6290000081062317}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.803600013256073},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.7621999979019165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7476999759674072},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7246999740600586},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6349999904632568},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.5612000226974487},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5077999830245972},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.48840001225471497},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4634000062942505},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3955000042915344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.392300009727478},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3894999921321869},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3788999915122986},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3781000077724457},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.37139999866485596},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.35269999504089355},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3481999933719635},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.2944999933242798},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2906999886035919},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.11591/ijai.v15.i5.pp4946-4960","doi":"https://doi.org/10.11591/ijai.v15.i5.pp4946-4960","is_oa":true,"landing_page_url":"https://doi.org/10.11591/ijai.v15.i5.pp4946-4960","pdf_url":"https://ijai.iaescore.com/index.php/IJAI/article/download/27714/15459","source":{"id":"https://openalex.org/S2764408626","display_name":"IAES International Journal of Artificial Intelligence","issn_l":"2089-4872","issn":["2089-4872","2252-8938"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315009","host_organization_name":"Institute of Advanced Engineering and Science (IAES)","host_organization_lineage":["https://openalex.org/P4310315009"],"host_organization_lineage_names":["Institute of Advanced Engineering and Science (IAES)"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IAES International Journal of Artificial Intelligence (IJ-AI)","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.11591/ijai.v15.i5.pp4946-4960","doi":"https://doi.org/10.11591/ijai.v15.i5.pp4946-4960","is_oa":true,"landing_page_url":"https://doi.org/10.11591/ijai.v15.i5.pp4946-4960","pdf_url":"https://ijai.iaescore.com/index.php/IJAI/article/download/27714/15459","source":{"id":"https://openalex.org/S2764408626","display_name":"IAES International Journal of Artificial Intelligence","issn_l":"2089-4872","issn":["2089-4872","2252-8938"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315009","host_organization_name":"Institute of Advanced Engineering and Science (IAES)","host_organization_lineage":["https://openalex.org/P4310315009"],"host_organization_lineage_names":["Institute of Advanced Engineering and Science (IAES)"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IAES International Journal of Artificial Intelligence (IJ-AI)","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7221454792.pdf","grobid_xml":"https://content.openalex.org/works/W7221454792.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W2996981924","https://openalex.org/W3014871302","https://openalex.org/W3041133507","https://openalex.org/W3163587844","https://openalex.org/W3208140829","https://openalex.org/W3208848815","https://openalex.org/W4210728791","https://openalex.org/W4320197069","https://openalex.org/W4376607143","https://openalex.org/W4386301261","https://openalex.org/W4388496068","https://openalex.org/W4388817612","https://openalex.org/W4389080631","https://openalex.org/W4391130440","https://openalex.org/W4392488355","https://openalex.org/W4399695759","https://openalex.org/W4402655955","https://openalex.org/W4403010191","https://openalex.org/W4403572481","https://openalex.org/W4404223060","https://openalex.org/W4405022621","https://openalex.org/W4406522678","https://openalex.org/W4407012599","https://openalex.org/W4412470771","https://openalex.org/W4415369665","https://openalex.org/W4415861835","https://openalex.org/W7124875835"],"related_works":["https://openalex.org/W7103650390","https://openalex.org/W1598001448","https://openalex.org/W4210589760","https://openalex.org/W7154981420","https://openalex.org/W7126246231","https://openalex.org/W7128041956","https://openalex.org/W4412472741","https://openalex.org/W2551624499","https://openalex.org/W7172473622","https://openalex.org/W4307552296"],"abstract_inverted_index":{"Household":[0],"object":[1,30],"recognition":[2,31,96],"remains":[3],"a":[4,72,99,176],"challenging":[5],"task":[6],"in":[7,184,191],"robotics":[8,186],"due":[9],"to":[10,27,56,63,187],"environmental":[11],"disturbances":[12],"like":[13],"varying":[14],"illumination":[15,90],"conditions.":[16],"This":[17,130,173],"study":[18],"investigates":[19],"the":[20,47,53,95,109,116,134,139,154],"utilization":[21],"of":[22,52,75,124,148,165],"standalone":[23],"near-infrared":[24],"(NIR)":[25],"imaging":[26],"mitigate":[28],"household":[29,185],"challenges":[32],"across":[33,88,122,169],"20":[34],"distinct":[35],"classes":[36],"under":[37],"diverse":[38],"lighting":[39],"scenarios.":[40,172],"Crucially,":[41],"this":[42,92],"research":[43,93,131,174],"focuses":[44],"on":[45,71,108],"evaluating":[46],"isolated,":[48],"single-channel":[49],"baseline":[50],"capacity":[51],"NIR":[54,156,181],"spectrum":[55,182],"explicitly":[57],"establish":[58],"its":[59],"independent":[60],"robustness":[61],"prior":[62],"introducing":[64],"complex":[65],"multimodal":[66],"architectural":[67],"fusion":[68],"frameworks.":[69],"Based":[70],"total":[73],"dataset":[74],"73,269":[76],"synchronized":[77],"images":[78],"(36,631":[79],"red,":[80],"green,":[81],"blue":[82],"(RGB)":[83],"and":[84,127],"36,638":[85],"NIR)":[86],"captured":[87],"variable":[89],"states,":[91],"modeled":[94],"process":[97],"using":[98],"convolutional":[100],"neural":[101],"network":[102,111],"(CNN)":[103],"with":[104],"transfer":[105],"learning":[106],"based":[107],"efficient":[110],"(EfficientNet)":[112],"architecture.":[113],"To":[114],"evaluate":[115],"model's":[117],"capabilities,":[118],"we":[119],"tested":[120],"performance":[121],"variations":[123],"dim":[125],"white":[126],"RGB":[128,141],"light.":[129],"reveals":[132],"that":[133],"NIR-based":[135],"model":[136,157],"significantly":[137],"outperforms":[138],"standard":[140],"baseline,":[142],"which":[143],"achieved":[144],"an":[145,162],"average":[146,163],"accuracy":[147,164],"(64.55":[149],"\u00b1":[150,167],"24.32)%.":[151],"In":[152],"contrast,":[153],"investigative":[155],"maintained":[158],"high":[159],"robustness,":[160],"achieving":[161],"(95.85":[166],"3.08)%":[168],"all":[170],"testing":[171],"establishes":[175],"robust":[177],"foundation":[178],"for":[179],"implementing":[180],"analysis":[183],"enhance":[188],"operational":[189],"reliability":[190],"real-world":[192],"environments.":[193]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-10-12T00:00:00"}
