{"id":"https://openalex.org/W4411639767","doi":"https://doi.org/10.1109/tii.2025.3578136","title":"CLMFNet: Cross-Level Multimodal Fusion Network for RGB-T Semantic Segmentation of Distribution Network Lines","display_name":"CLMFNet: Cross-Level Multimodal Fusion Network for RGB-T Semantic Segmentation of Distribution Network Lines","publication_year":2025,"publication_date":"2025-06-25","ids":{"openalex":"https://openalex.org/W4411639767","doi":"https://doi.org/10.1109/tii.2025.3578136"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2025.3578136","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3578136","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Industrial Informatics","raw_type":"journal-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/A5000360043","display_name":"Rui Du","orcid":"https://orcid.org/0000-0002-3811-7488"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Du","raw_affiliation_strings":["School of Robotics, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-3811-7488","affiliations":[{"raw_affiliation_string":"School of Robotics, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100323420","display_name":"Hui Zhang","orcid":"https://orcid.org/0000-0002-1803-3148"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Zhang","raw_affiliation_strings":["School of Robotics, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-1803-3148","affiliations":[{"raw_affiliation_string":"School of Robotics, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084391120","display_name":"Hang Zhong","orcid":"https://orcid.org/0000-0001-5893-5026"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Zhong","raw_affiliation_strings":["School of Robotics, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-5893-5026","affiliations":[{"raw_affiliation_string":"School of Robotics, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063874284","display_name":"Zhihong Huang","orcid":"https://orcid.org/0000-0003-0549-1059"},"institutions":[{"id":"https://openalex.org/I4210122501","display_name":"Hunan Xiangdian Test Research Institute (China)","ror":"https://ror.org/0391pty66","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210122501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihong Huang","raw_affiliation_strings":["State Grid Hunan Electric Power Company Electric Power Research Institute, and Hunan Province Xiangdian Electric Power Experimental Research Institute, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Hunan Electric Power Company Electric Power Research Institute, and Hunan Province Xiangdian Electric Power Experimental Research Institute, Changsha, China","institution_ids":["https://openalex.org/I4210122501"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025640070","display_name":"Yaonan Wang","orcid":"https://orcid.org/0000-0002-0519-6458"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaonan Wang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0519-6458","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5239,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.84275397,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"21","issue":"10","first_page":"7632","last_page":"7642"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9828000068664551,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9828000068664551,"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/T14276","display_name":"Power Systems and Technologies","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.95660001039505,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/computer-science","display_name":"Computer science","score":0.6191043257713318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5879819393157959},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5668761730194092},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.559661865234375},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42612242698669434},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4256206154823303},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3712661862373352},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3457692265510559}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6191043257713318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5879819393157959},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5668761730194092},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.559661865234375},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42612242698669434},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4256206154823303},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3712661862373352},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3457692265510559},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2025.3578136","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2025.3578136","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7185484708","display_name":null,"funder_award_id":"62027810","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2111310121","https://openalex.org/W2305269547","https://openalex.org/W2589061485","https://openalex.org/W2734927467","https://openalex.org/W2774839435","https://openalex.org/W2896014703","https://openalex.org/W2921749009","https://openalex.org/W2953267880","https://openalex.org/W2981071629","https://openalex.org/W2999092571","https://openalex.org/W3033020497","https://openalex.org/W3034606961","https://openalex.org/W3095598260","https://openalex.org/W3105129182","https://openalex.org/W3129245048","https://openalex.org/W3146497429","https://openalex.org/W3160028740","https://openalex.org/W3170885821","https://openalex.org/W3178086535","https://openalex.org/W3198062544","https://openalex.org/W4220745223","https://openalex.org/W4226155060","https://openalex.org/W4285163934","https://openalex.org/W4288391270","https://openalex.org/W4307771365","https://openalex.org/W4312376179","https://openalex.org/W4319879007","https://openalex.org/W4353004354","https://openalex.org/W4362714628","https://openalex.org/W4366378388","https://openalex.org/W4381300351","https://openalex.org/W4385757652","https://openalex.org/W4386179772","https://openalex.org/W4387449279","https://openalex.org/W4388017447","https://openalex.org/W4388919406","https://openalex.org/W4389664527"],"related_works":["https://openalex.org/W2486460843","https://openalex.org/W2168109476","https://openalex.org/W1968121071","https://openalex.org/W2061647633","https://openalex.org/W4379231730","https://openalex.org/W2020254986","https://openalex.org/W2686985752","https://openalex.org/W1992540108","https://openalex.org/W4389858081","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Accurate":[0],"semantic":[1,81,169],"segmentation":[2,62,82,170],"is":[3,57,72,92,120],"crucial":[4],"in":[5,94,150,167,171],"distribution":[6,174],"network":[7,70],"line":[8],"monitoring":[9],"to":[10,18,36,59,74,96,122],"ensure":[11],"the":[12,19,22,25,47,76,124],"system\u2019s":[13],"reliability":[14],"and":[15,24,52,78,86,102,126,141,158],"security.":[16],"Due":[17],"complexity":[20],"of":[21,27,50,80,128],"environment":[23],"diversity":[26],"devices,":[28],"unimodal":[29],"images":[30,56],"(such":[31],"as":[32,154],"RGB":[33,51,85,101],"images)":[34],"struggle":[35],"provide":[37],"enough":[38],"information":[39],"for":[40],"effective":[41],"segmentation.":[42],"To":[43],"address":[44],"these":[45],"challenges,":[46],"complementary":[48],"nature":[49],"thermal":[53],"infrared":[54],"(TIR)":[55],"leveraged":[58],"significantly":[60],"enhance":[61],"performance.":[63],"Therefore,":[64],"an":[65],"innovative":[66],"cross-level":[67],"multimodal":[68,112],"fusion":[69,113],"(CLMFNet)":[71],"proposed":[73],"improve":[75],"accuracy":[77,156],"robustness":[79],"by":[83],"integrating":[84],"TIR":[87,103],"data.":[88],"A":[89],"dual-branch":[90],"architecture":[91],"employed":[93],"CLMFNet":[95,133],"extract":[97],"features":[98,129],"from":[99],"both":[100],"images,":[104],"which":[105],"are":[106],"then":[107],"effectively":[108],"integrated":[109],"through":[110],"a":[111,116,137],"strategy.":[114],"Additionally,":[115],"cross-layer":[117],"guidance":[118],"mechanism":[119],"introduced":[121],"facilitate":[123],"complementation":[125],"optimization":[127],"across":[130],"different":[131],"levels.":[132],"was":[134],"validated":[135],"on":[136],"custom":[138],"RGB-T":[139],"dataset,":[140],"experimental":[142],"results":[143],"showed":[144],"that":[145],"it":[146],"outperformed":[147],"state-of-the-art":[148],"methods":[149],"key":[151],"metrics":[152],"such":[153],"mean":[155,159],"(mAcc)":[157],"intersection":[160],"over":[161],"union":[162],"(mIoU),":[163],"demonstrating":[164],"its":[165],"effectiveness":[166],"performing":[168],"complex":[172],"power":[173],"scenarios.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}