{"id":"https://openalex.org/W4318478874","doi":"https://doi.org/10.3390/s23031527","title":"An Adaptive Kernels Layer for Deep Neural Networks Based on Spectral Analysis for Image Applications","display_name":"An Adaptive Kernels Layer for Deep Neural Networks Based on Spectral Analysis for Image Applications","publication_year":2023,"publication_date":"2023-01-30","ids":{"openalex":"https://openalex.org/W4318478874","doi":"https://doi.org/10.3390/s23031527","pmid":"https://pubmed.ncbi.nlm.nih.gov/36772565"},"language":"en","primary_location":{"id":"doi:10.3390/s23031527","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23031527","pdf_url":"https://www.mdpi.com/1424-8220/23/3/1527/pdf?version=1675077716","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/3/1527/pdf?version=1675077716","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006218211","display_name":"Tariq Al Shoura","orcid":"https://orcid.org/0000-0002-0421-7464"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Tariq Al Shoura","raw_affiliation_strings":["Department of Electrical and Software Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada"],"raw_orcid":"https://orcid.org/0000-0002-0421-7464","affiliations":[{"raw_affiliation_string":"Department of Electrical and Software Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061884304","display_name":"Henry Leung","orcid":"https://orcid.org/0000-0002-5984-107X"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Henry Leung","raw_affiliation_strings":["Department of Electrical and Software Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Software Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013633199","display_name":"Bhashyam Balaji","orcid":"https://orcid.org/0000-0002-1868-9470"},"institutions":[{"id":"https://openalex.org/I1297460800","display_name":"Defence Research and Development Canada","ror":"https://ror.org/00hgy8d33","country_code":"CA","type":"government","lineage":["https://openalex.org/I1297460800","https://openalex.org/I1336338359","https://openalex.org/I2802286613"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Bhashyam Balaji","raw_affiliation_strings":["Radar Sensing and Exploitation Section, Defence Research and Development Canada, Ottawa, ON K1A 0Z4, Canada"],"raw_orcid":"https://orcid.org/0000-0002-1868-9470","affiliations":[{"raw_affiliation_string":"Radar Sensing and Exploitation Section, Defence Research and Development Canada, Ottawa, ON K1A 0Z4, Canada","institution_ids":["https://openalex.org/I1297460800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006218211"],"corresponding_institution_ids":["https://openalex.org/I168635309"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":0.2158,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47942617,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"23","issue":"3","first_page":"1527","last_page":"1527"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"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":0.9995999932289124,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9993000030517578,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9983999729156494,"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/computer-science","display_name":"Computer science","score":0.7604780197143555},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6992554664611816},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6757112741470337},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6136583089828491},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5613620281219482},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5385398268699646},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4884549677371979},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4692789316177368},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.45121151208877563},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.4373414218425751},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3631054759025574},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1344638168811798}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7604780197143555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6992554664611816},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6757112741470337},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6136583089828491},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5613620281219482},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5385398268699646},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4884549677371979},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4692789316177368},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.45121151208877563},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.4373414218425751},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3631054759025574},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1344638168811798},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s23031527","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23031527","pdf_url":"https://www.mdpi.com/1424-8220/23/3/1527/pdf?version=1675077716","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:36772565","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36772565","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9921880","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9921880","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:41d79768111c404c867a3e0c3295933b","is_oa":true,"landing_page_url":"https://doaj.org/article/41d79768111c404c867a3e0c3295933b","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":"Sensors, Vol 23, Iss 3, p 1527 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/3/1527/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23031527","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23031527","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23031527","pdf_url":"https://www.mdpi.com/1424-8220/23/3/1527/pdf?version=1675077716","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4318478874.pdf"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1977295328","https://openalex.org/W2015780366","https://openalex.org/W2097117768","https://openalex.org/W2112796928","https://openalex.org/W2144982973","https://openalex.org/W2163605009","https://openalex.org/W2172189177","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2531634031","https://openalex.org/W2610691757","https://openalex.org/W2910587630","https://openalex.org/W2928133111","https://openalex.org/W2962766617","https://openalex.org/W2964350391","https://openalex.org/W2972255615","https://openalex.org/W2988020997","https://openalex.org/W3000429716","https://openalex.org/W3036616251","https://openalex.org/W3040020917","https://openalex.org/W3089642182","https://openalex.org/W3196289623","https://openalex.org/W4283782987","https://openalex.org/W4287220076","https://openalex.org/W4303982380","https://openalex.org/W4307552305","https://openalex.org/W4309705228","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2337415362","https://openalex.org/W4312857205","https://openalex.org/W121273120","https://openalex.org/W2740820121","https://openalex.org/W317572212","https://openalex.org/W2002009170","https://openalex.org/W2034462085","https://openalex.org/W2546871836","https://openalex.org/W2141888456","https://openalex.org/W1604511055"],"abstract_inverted_index":{"As":[0],"the":[1,10,14,36,51,76,79,83,123,129,149,155,197,207,212,258],"pixel":[2],"resolution":[3,126],"of":[4,16,78,119,151,184,193,196,203,206,261],"imaging":[5],"equipment":[6],"has":[7],"grown":[8],"larger,":[9,246],"images\u2019":[11,108],"sizes":[12,109],"and":[13,41,89,145,154,160,227,240],"number":[15,260],"pixels":[17],"used":[18],"to":[19,61,107,112,143,174,190,221,232,248],"represent":[20],"objects":[21,144],"in":[22,110,178,236,252,254],"images":[23,34,84,118,183,244],"have":[24,60],"increased":[25],"accordingly,":[26],"exposing":[27],"an":[28,95,102],"issue":[29],"when":[30],"dealing":[31],"with":[32,200],"larger":[33],"using":[35,148,169],"traditional":[37],"deep":[38],"learning":[39],"models":[40],"methods,":[42],"as":[43,49,66,86,101,225,243],"they":[44],"typically":[45],"employ":[46],"mechanisms":[47],"such":[48,65,85,224],"increasing":[50],"models\u2019":[52],"depth,":[53],"which,":[54],"while":[55],"suitable":[56],"for":[57,71,134,216,257],"applications":[58,72,219],"that":[59,73,104,140],"be":[62],"spatially":[63],"invariant,":[64],"image":[67,136,218,237],"classification,":[68],"causes":[69],"issues":[70],"relies":[74],"on":[75],"location":[77],"different":[80,120],"features":[81,146],"within":[82],"object":[87,255],"localization":[88,256],"change":[90],"detection.":[91],"This":[92],"paper":[93],"proposes":[94],"adaptive":[96],"convolutional":[97],"kernels":[98],"layer":[99],"(AKL)":[100],"architecture":[103],"adjusts":[105],"dynamically":[106],"order":[111],"extract":[113],"comparable":[114],"spectral":[115,158,179,198],"information":[116,180],"from":[117],"sizes,":[121,186],"improving":[122],"features\u2019":[124],"spatial":[125],"without":[127],"sacrificing":[128],"local":[130],"receptive":[131],"field":[132],"(LRF)":[133],"various":[135,185,217],"applications,":[137,239],"specifically":[138],"those":[139],"are":[141],"sensitive":[142],"locations,":[147],"definition":[150],"Fourier":[152],"transform":[153],"relation":[156],"between":[157],"analysis":[159],"convolution":[161],"kernels.":[162],"The":[163],"proposed":[164],"method":[165],"is":[166,214],"then":[167],"tested":[168],"a":[170,194,201,249],"Monte":[171],"Carlo":[172],"simulation":[173],"evaluate":[175],"its":[176,188,230],"performance":[177],"coverage":[181,192,209],"across":[182],"validating":[187],"ability":[189],"maintain":[191],"ratio":[195],"domain":[199],"variation":[202],"around":[204],"20%":[205],"desired":[208],"ratio.":[210],"Finally,":[211],"AKL":[213],"validated":[215],"compared":[220],"other":[222],"architectures":[223],"Inception":[226,234],"VGG,":[228],"demonstrating":[229],"capability":[231],"match":[233],"v4":[235],"classification":[238],"outperforms":[241],"it":[242],"grow":[245],"up":[247],"30%":[250],"increase":[251],"accuracy":[253],"same":[259],"parameters.":[262]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
