{"id":"https://openalex.org/W7155686077","doi":"https://doi.org/10.1007/s44163-026-01243-x","title":"Image splicing and semantic segmentation\u2013based omni-directional monitoring for substation equipment","display_name":"Image splicing and semantic segmentation\u2013based omni-directional monitoring for substation equipment","publication_year":2026,"publication_date":"2026-04-26","ids":{"openalex":"https://openalex.org/W7155686077","doi":"https://doi.org/10.1007/s44163-026-01243-x"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-026-01243-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-01243-x","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"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":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1007/s44163-026-01243-x","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134645743","display_name":"Ning Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]},{"id":"https://openalex.org/I4210126065","display_name":"Shanghai Electric (China)","ror":"https://ror.org/0314qy595","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210126065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ning Chen","raw_affiliation_strings":["State Grid Shanghai Extra High Voltage Company, Shanghai, 200063, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Shanghai Extra High Voltage Company, Shanghai, 200063, China","institution_ids":["https://openalex.org/I4210126065","https://openalex.org/I17442442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134627142","display_name":"Xin Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]},{"id":"https://openalex.org/I4210126065","display_name":"Shanghai Electric (China)","ror":"https://ror.org/0314qy595","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210126065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Yang","raw_affiliation_strings":["State Grid Shanghai Extra High Voltage Company, Shanghai, 200063, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Shanghai Extra High Voltage Company, Shanghai, 200063, China","institution_ids":["https://openalex.org/I4210126065","https://openalex.org/I17442442"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085885504","display_name":"\u660c\u6d2a\u65b0","orcid":null},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]},{"id":"https://openalex.org/I4210126065","display_name":"Shanghai Electric (China)","ror":"https://ror.org/0314qy595","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210126065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxin Chang","raw_affiliation_strings":["State Grid Shanghai Extra High Voltage Company, Shanghai, 200063, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Shanghai Extra High Voltage Company, Shanghai, 200063, China","institution_ids":["https://openalex.org/I4210126065","https://openalex.org/I17442442"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5134645743"],"corresponding_institution_ids":["https://openalex.org/I17442442","https://openalex.org/I4210126065"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44414854,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13715","display_name":"Power Line Inspection Robots","score":0.5583000183105469,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T13715","display_name":"Power Line Inspection Robots","score":0.5583000183105469,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.041200000792741776,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.036400001496076584,"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/image","display_name":"Image (mathematics)","score":0.47760000824928284},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3603000044822693},{"id":"https://openalex.org/keywords/rna-splicing","display_name":"RNA splicing","score":0.328000009059906},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.2777999937534332},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.26429998874664307}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6140000224113464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49000000953674316},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47760000824928284},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4390000104904175},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3603000044822693},{"id":"https://openalex.org/C54458228","wikidata":"https://www.wikidata.org/wiki/Q237218","display_name":"RNA splicing","level":4,"score":0.328000009059906},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2777999937534332},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.24869999289512634}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-026-01243-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-01243-x","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"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":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9a7b3d97f6c1424ca5e55078bb89a6ac","is_oa":true,"landing_page_url":"https://doaj.org/article/9a7b3d97f6c1424ca5e55078bb89a6ac","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":"Discover Artificial Intelligence, Vol 6, Iss 1 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-026-01243-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-01243-x","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"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":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W4293224618","https://openalex.org/W4318483790","https://openalex.org/W4378195006","https://openalex.org/W4382936454","https://openalex.org/W4385507047","https://openalex.org/W4387435771","https://openalex.org/W4389078336","https://openalex.org/W4389098452","https://openalex.org/W4389767241","https://openalex.org/W4391316866","https://openalex.org/W4392359405","https://openalex.org/W4392382888","https://openalex.org/W4393159321","https://openalex.org/W4395469756","https://openalex.org/W4396927287","https://openalex.org/W4399589632","https://openalex.org/W4400226592","https://openalex.org/W4400576739","https://openalex.org/W4400741202","https://openalex.org/W4401360527","https://openalex.org/W4401544964","https://openalex.org/W4401865327","https://openalex.org/W4402200621","https://openalex.org/W4402491454","https://openalex.org/W4402533914","https://openalex.org/W4402607066","https://openalex.org/W4403767861","https://openalex.org/W4405001789","https://openalex.org/W4405487666","https://openalex.org/W4406457853","https://openalex.org/W4406460165","https://openalex.org/W4407665845","https://openalex.org/W4407778834","https://openalex.org/W4407779005","https://openalex.org/W4407843147","https://openalex.org/W4407964283","https://openalex.org/W4408792077","https://openalex.org/W4408898930","https://openalex.org/W4409669420","https://openalex.org/W4414037001","https://openalex.org/W4416790988"],"related_works":[],"abstract_inverted_index":{"Aiming":[0],"at":[1,64,165],"the":[2,27,52,56,67,79,102,112,124,129,150,166,171],"problems":[3,71],"of":[4,11,16,22,33,115,118,123,156,174],"restricted":[5],"video":[6],"monitoring":[7,42],"angles,":[8],"significant":[9],"traces":[10],"image":[12,46,157],"splicing,":[13],"insufficient":[14],"coverage":[15],"equipment":[17,41,141,161],"detection,":[18],"and":[19,30,48,58,69,78,97,99,106,128,160,164,182],"low":[20],"efficiency":[21],"inspection":[23],"report":[24],"generation":[25],"in":[26,139,154],"unattended":[28],"operation":[29],"maintenance":[31],"process":[32],"intelligent":[34],"substations,":[35],"this":[36],"paper":[37],"proposes":[38],"a":[39],"panoramic":[40,140],"method":[43,151],"that":[44,149],"integrates":[45],"splicing":[47,126],"semantic":[49,91,130],"segmentation.":[50],"Through":[51],"multi-stage":[53,125],"fusion":[54,70],"strategy,":[55,109],"infrared":[57],"visible":[59],"images":[60,74,81],"are":[61,75,86,133],"accurately":[62],"spliced":[63],"different":[65],"scales,":[66],"alignment":[68],"between":[72],"heterogeneous":[73],"effectively":[76],"solved,":[77],"immersive":[80],"with":[82,101],"high":[83],"visual":[84],"consistency":[85],"generated.":[87],"The":[88,143],"deep":[89],"learning-based":[90],"segmentation":[92,131],"model":[93],"is":[94],"further":[95],"constructed":[96],"optimized,":[98],"combined":[100],"migration":[103],"training":[104],"mechanism":[105],"optimized":[107],"suppression":[108],"to":[110,135],"complete":[111],"fine-grained":[113],"recognition":[114],"various":[116],"types":[117],"electrical":[119],"equipment.":[120],"Detailed":[121],"descriptions":[122],"framework":[127],"pipeline":[132],"provided":[134],"clarify":[136],"their":[137],"roles":[138],"perception.":[142],"actual":[144],"engineering":[145,183],"application":[146],"results":[147],"show":[148],"performs":[152],"well":[153],"terms":[155],"processing":[158],"accuracy":[159],"detection":[162],"accuracy,":[163],"same":[167],"time":[168],"significantly":[169],"improves":[170],"automation":[172],"level":[173],"remote":[175],"inspection,":[176],"which":[177],"has":[178],"good":[179],"promotion":[180],"prospects":[181],"practical":[184],"value.":[185]},"counts_by_year":[],"updated_date":"2026-06-10T06:17:36.459440","created_date":"2026-04-27T00:00:00"}