{"id":"https://openalex.org/W4410582980","doi":"https://doi.org/10.1109/access.2025.3572294","title":"A Novel Dilated Convolution Light Weight Neural Network (DCLW-NN) for the Classification of Breast Thermograms","display_name":"A Novel Dilated Convolution Light Weight Neural Network (DCLW-NN) for the Classification of Breast Thermograms","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410582980","doi":"https://doi.org/10.1109/access.2025.3572294"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3572294","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3572294","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3572294","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081351049","display_name":"S. Malathi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"S. Malathi","raw_affiliation_strings":["Department of Electronics and Communication Engineering, National Engineering College, Kovilpatti, India"],"raw_orcid":"https://orcid.org/0000-0001-7569-6848","affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, National Engineering College, Kovilpatti, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090774030","display_name":"A. Shenbagavalli","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. Shenbagavalli","raw_affiliation_strings":["Department of Electronics and Communication Engineering, National Engineering College, Kovilpatti, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, National Engineering College, Kovilpatti, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043209594","display_name":"N. Sriraam","orcid":"https://orcid.org/0000-0003-3790-3900"},"institutions":[{"id":"https://openalex.org/I4405260736","display_name":"Dayananda Sagar College of Engineering","ror":"https://ror.org/046qksq74","country_code":"IN","type":"education","lineage":["https://openalex.org/I4400573291","https://openalex.org/I4405260736"]},{"id":"https://openalex.org/I8977528","display_name":"Dr. Hari Singh Gour University","ror":"https://ror.org/01xapxe37","country_code":"IN","type":"education","lineage":["https://openalex.org/I8977528"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"N. Sriraam","raw_affiliation_strings":["Department of Medical Electronics Engineering, Dayananda Sagar College of Engineering, Bengaluru, India","Department of Medical Electronics Engineering, Dayananda sagar college of engineering, Bangalore, India"],"raw_orcid":"https://orcid.org/0000-0003-3790-3900","affiliations":[{"raw_affiliation_string":"Department of Medical Electronics Engineering, Dayananda Sagar College of Engineering, Bengaluru, India","institution_ids":["https://openalex.org/I4405260736","https://openalex.org/I8977528"]},{"raw_affiliation_string":"Department of Medical Electronics Engineering, Dayananda sagar college of engineering, Bangalore, India","institution_ids":["https://openalex.org/I4405260736","https://openalex.org/I8977528"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2075,"currency":"USD","value_usd":2075},"apc_paid":{"value":2075,"currency":"USD","value_usd":2075},"fwci":1.898,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.84923299,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"98806","last_page":"98821"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12994","display_name":"Infrared Thermography in Medicine","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T12994","display_name":"Infrared Thermography in Medicine","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7199978828430176},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6289821863174438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5452715158462524},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5397987365722656},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5308542847633362}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7199978828430176},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6289821863174438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5452715158462524},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5397987365722656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5308542847633362}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3572294","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3572294","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7bd2c8d25ed84bff9a1a41f40e48ded9","is_oa":true,"landing_page_url":"https://doaj.org/article/7bd2c8d25ed84bff9a1a41f40e48ded9","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":"IEEE Access, Vol 13, Pp 98806-98821 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3572294","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3572294","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1450963973","https://openalex.org/W2062177968","https://openalex.org/W2102017903","https://openalex.org/W2127063408","https://openalex.org/W2270296303","https://openalex.org/W2378701766","https://openalex.org/W2749594344","https://openalex.org/W2766442486","https://openalex.org/W2766973697","https://openalex.org/W2777186991","https://openalex.org/W2884274016","https://openalex.org/W2900452647","https://openalex.org/W2908252355","https://openalex.org/W2942590749","https://openalex.org/W2942803597","https://openalex.org/W2946053491","https://openalex.org/W2970091429","https://openalex.org/W2981803692","https://openalex.org/W2997292990","https://openalex.org/W2997797021","https://openalex.org/W2997816193","https://openalex.org/W3009928129","https://openalex.org/W3015320572","https://openalex.org/W3022192153","https://openalex.org/W3035888744","https://openalex.org/W3092028788","https://openalex.org/W3121829632","https://openalex.org/W3127390459","https://openalex.org/W3133988528","https://openalex.org/W3143173588","https://openalex.org/W3144825495","https://openalex.org/W3152732431","https://openalex.org/W3156242811","https://openalex.org/W3168198489","https://openalex.org/W3188452244","https://openalex.org/W3190820488","https://openalex.org/W3196132393","https://openalex.org/W4321446289","https://openalex.org/W4323644096","https://openalex.org/W4396578191","https://openalex.org/W4405372163","https://openalex.org/W4406524338"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Breast":[0],"cancer":[1],"poses":[2],"lots":[3],"of":[4,55,92,147,170,188,194,205,211,233,236,240],"challenges":[5],"in":[6,72],"the":[7,18,38,52,77,90,99,140,145,150,167,171,186,195,201,206,212],"medical":[8],"fraternity":[9],"worldwide.":[10],"Hence,":[11],"it":[12,225,229],"requires":[13],"early":[14],"diagnosis":[15],"to":[16,36,50,58,75],"treat":[17],"affected":[19],"people.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24],"have":[25],"presented":[26],"a":[27,46,64,95,102],"novel":[28],"Dilated":[29],"Convolution":[30,88],"Light":[31],"Weight":[32],"Neural":[33,42],"Network":[34,43],"(DCLW-NN)":[35],"analyze":[37],"breast":[39],"thermograms.":[40],"Convolutional":[41],"(CNN)":[44],"is":[45,63,108,124,152,164,174,197],"deep":[47],"learning":[48],"model":[49,78,107,123,151,173,196,214],"process":[51],"hierarchical":[53],"feature":[54],"visual":[56],"data":[57,148],"conduct":[59],"image":[60],"classification.":[61],"DCLW-NN":[62,189],"light":[65],"weight":[66],"architecture":[67,219],"that":[68,228],"uses":[69],"dilation":[70],"principle":[71],"standard":[73],"convolution":[74],"reduce":[76,84],"parameters":[79,204],"and":[80,119,131,135,138,161,184,224,238],"maintain":[81],"accuracy.":[82,142],"To":[83,143],"system":[85],"complexity,":[86],"dilated":[87],"enables":[89],"integration":[91],"information":[93],"from":[94],"wider":[96],"range":[97],"without":[98],"need":[100],"for":[101],"large":[103],"kernel.":[104],"The":[105,122,191,208],"proposed":[106,213],"experimented":[109],"with":[110,133,155,176,181,217],"two":[111],"different":[112],"infrared":[113],"thermography":[114],"imaging":[115],"datasets":[116,137,156],"like":[117,220],"DMR-IR":[118],"Proprietary":[120],"Datasets.":[121],"tested":[125],"under":[126],"four":[127],"cases":[128],"by":[129,199],"training":[130],"testing":[132],"similar":[134],"dissimilar":[136],"obtain":[139],"classification":[141],"solve":[144],"problem":[146],"scarcity,":[149],"worked":[153],"out":[154],"at":[157],"various":[158],"augmentation":[159],"level":[160],"their":[162],"performance":[163,210],"compared.":[165],"Lastly,":[166],"categorization":[168],"layer":[169],"CNN":[172],"replaced":[175],"Support":[177],"Vector":[178],"Machine(SVM)":[179],"classifier":[180,209],"L2":[182],"regularization":[183],"found":[185,227],"prospects":[187],"Classifier.":[190],"significant":[192],"improvement":[193],"obtained":[198],"varying":[200],"hyper":[202],"tuning":[203],"model.":[207],"was":[215,226],"compared":[216],"existing":[218],"RESNET-50,":[221],"AlexNet,":[222],"VGG-16":[223],"produces":[230],"better":[231],"accuracy":[232],"99%,":[234],"Sensitivity":[235],"100%":[237],"Specificity":[239],"98%.":[241]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
