{"id":"https://openalex.org/W4317515944","doi":"https://doi.org/10.1109/ccis57298.2022.10016321","title":"An Efficient End-to-End CNN Network for High-voltage Transmission Line Segmentation","display_name":"An Efficient End-to-End CNN Network for High-voltage Transmission Line Segmentation","publication_year":2022,"publication_date":"2022-11-26","ids":{"openalex":"https://openalex.org/W4317515944","doi":"https://doi.org/10.1109/ccis57298.2022.10016321"},"language":"en","primary_location":{"id":"doi:10.1109/ccis57298.2022.10016321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis57298.2022.10016321","pdf_url":null,"source":{"id":"https://openalex.org/S4363608348","display_name":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","raw_type":"proceedings-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/A5100698159","display_name":"Lei Yang","orcid":"https://orcid.org/0000-0003-1212-9445"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lei Yang","raw_affiliation_strings":["Zhengzhou University,School of Electrical and Information Engineering,China,450001"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University,School of Electrical and Information Engineering,China,450001","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002006897","display_name":"Shuyi Kong","orcid":"https://orcid.org/0000-0002-0808-9690"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyi Kong","raw_affiliation_strings":["Zhengzhou University,School of Electrical and Information Engineering,China,450001"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University,School of Electrical and Information Engineering,China,450001","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052344898","display_name":"Shilong Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilong Cui","raw_affiliation_strings":["Zhengzhou University,School of Electrical and Information Engineering,China,450001"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University,School of Electrical and Information Engineering,China,450001","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067869982","display_name":"Hanyun Huang","orcid":"https://orcid.org/0000-0001-9875-262X"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanyun Huang","raw_affiliation_strings":["Zhengzhou University,School of Electrical and Information Engineering,China,450001"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University,School of Electrical and Information Engineering,China,450001","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006721216","display_name":"Yanhong Liu","orcid":"https://orcid.org/0000-0002-7349-5871"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhong Liu","raw_affiliation_strings":["Zhengzhou University,School of Electrical and Information Engineering,China,450001"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University,School of Electrical and Information Engineering,China,450001","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100698159"],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":0.0599,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.34963639,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"565","last_page":"570"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9972000122070312,"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":0.9972000122070312,"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/T13715","display_name":"Power Line Inspection Robots","score":0.9925000071525574,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9898999929428101,"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":0.8290653824806213},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7546606063842773},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6580051183700562},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6064950227737427},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5116072297096252},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48555776476860046},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4728658199310303},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4642302393913269},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4435599446296692},{"id":"https://openalex.org/keywords/electric-power-transmission","display_name":"Electric power transmission","score":0.427263468503952},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.4215978682041168},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4205303490161896},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4174363911151886},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3227108418941498},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14495301246643066},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1003778874874115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8290653824806213},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7546606063842773},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6580051183700562},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6064950227737427},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5116072297096252},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48555776476860046},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4728658199310303},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4642302393913269},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4435599446296692},{"id":"https://openalex.org/C140311924","wikidata":"https://www.wikidata.org/wiki/Q200928","display_name":"Electric power transmission","level":2,"score":0.427263468503952},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.4215978682041168},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4205303490161896},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4174363911151886},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3227108418941498},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14495301246643066},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1003778874874115},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccis57298.2022.10016321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis57298.2022.10016321","pdf_url":null,"source":{"id":"https://openalex.org/S4363608348","display_name":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2786324549","https://openalex.org/W2798122215","https://openalex.org/W2957682677","https://openalex.org/W2963881378","https://openalex.org/W2971657673","https://openalex.org/W3012251373","https://openalex.org/W3098650625","https://openalex.org/W3135328933","https://openalex.org/W3142788400","https://openalex.org/W3156655103","https://openalex.org/W3161081823","https://openalex.org/W3211350522","https://openalex.org/W4226183856","https://openalex.org/W4289752563","https://openalex.org/W6750469568"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W3211292372","https://openalex.org/W803346624"],"abstract_inverted_index":{"Automation":[0],"detection":[1,42,57,184],"of":[2,7,24,43,110,149,163,178,186],"power":[3,12],"transmission":[4,44],"lines":[5,45],"is":[6,97,117,142,170],"great":[8,48],"importance":[9],"for":[10],"intelligent":[11],"inspection,":[13],"which":[14,159],"could":[15],"well":[16],"serve":[17],"the":[18,107,108,121,126,131,137,183,195],"route":[19],"programming":[20],"and":[21,88,129,181],"motion":[22],"guidance":[23],"examination":[25],"platforms.":[26],"However,":[27],"due":[28],"to":[29,100,119,145,154,173],"complex":[30,34],"factors,":[31],"such":[32],"as":[33],"natural":[35],"environment,":[36],"illumination":[37],"change,":[38],"image":[39,72],"noise,":[40],"efficient":[41],"still":[46,65],"frontages":[47],"challenges.":[49],"Lately,":[50],"deep":[51],"learning":[52],"has":[53,66,200],"exhibited":[54],"a":[55,67,113,201],"good":[56,202],"effect":[58],"among":[59],"different":[60],"segmentation":[61,95,104,187,198,209],"tasks.":[62],"Nevertheless,":[63],"it":[64],"few":[68],"disadvantages":[69],"in":[70],"high-precision":[71],"segmentation,":[73],"like":[74],"inadequate":[75],"detection,":[76],"information":[77,156],"loss":[78,157],"caused":[79],"by":[80],"multiple":[81],"pooling":[82,164],"operations,":[83],"etc.":[84],"To":[85],"realize":[86,174],"automatic":[87],"accurate":[89],"pixel-level":[90],"extraction,":[91],"an":[92,102,166],"attention":[93,115,167,196],"fusion":[94,168,197],"network":[96,188,199],"put":[98,171],"forward":[99,172],"provide":[101],"end-to-end":[103],"module.":[105],"Considering":[106],"problem":[109],"class":[111],"imbalance,":[112],"global":[114],"model":[116],"introduced":[118],"make":[120],"module":[122],"focus":[123],"more":[124],"on":[125,189],"target":[127],"region":[128],"suppress":[130],"unimportant":[132],"features.":[133],"Meanwhile,":[134],"aimed":[135],"at":[136],"semantic":[138],"gap,":[139],"residual":[140],"path":[141],"also":[143],"proposed":[144],"achieve":[146],"effective":[147,175],"usage":[148],"local":[150],"information.":[151],"In":[152],"addition,":[153],"solve":[155],"issue":[158],"arise":[160],"from":[161],"plenty":[162],"processing,":[165],"block":[169],"feature":[176],"aggregation":[177],"multi-scale":[179,190],"features":[180],"improve":[182],"ability":[185],"objects.":[191],"Experiments":[192],"exhibit":[193],"that":[194],"extraction":[203],"capacity":[204],"compared":[205],"with":[206],"other":[207],"classical":[208],"network.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
