{"id":"https://openalex.org/W4394713333","doi":"https://doi.org/10.1109/ricai60863.2023.10488973","title":"An Infrastructure Segmentation Neural Network for UAV Remote Sensing Images","display_name":"An Infrastructure Segmentation Neural Network for UAV Remote Sensing Images","publication_year":2023,"publication_date":"2023-12-01","ids":{"openalex":"https://openalex.org/W4394713333","doi":"https://doi.org/10.1109/ricai60863.2023.10488973"},"language":"en","primary_location":{"id":"doi:10.1109/ricai60863.2023.10488973","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ricai60863.2023.10488973","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 5th International Conference on Robotics, Intelligent Control and Artificial Intelligence (RICAI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100622671","display_name":"Shuo Ma","orcid":"https://orcid.org/0000-0002-8324-0506"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Ma","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University,Jinan,China","School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University,Jinan,China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412323","display_name":"Xiaokang Zhang","orcid":"https://orcid.org/0000-0002-6127-4801"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaokang Zhang","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University,Jinan,China","School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University,Jinan,China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108919052","display_name":"Haojia Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojia Fan","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University,Jinan,China","School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University,Jinan,China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100416750","display_name":"Teng Li","orcid":"https://orcid.org/0000-0003-0111-0108"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Teng Li","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University,Jinan,China","School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University,Jinan,China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"226","last_page":"231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9645000100135803,"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"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9645000100135803,"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"}},{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9277999997138977,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9179999828338623,"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":0.7362420558929443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5797984600067139},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5759893655776978},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5665160417556763},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5596212148666382},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5348830223083496},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3912608027458191},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.16422370076179504}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7362420558929443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5797984600067139},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5759893655776978},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5665160417556763},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5596212148666382},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5348830223083496},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3912608027458191},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.16422370076179504}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ricai60863.2023.10488973","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ricai60863.2023.10488973","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 5th International Conference on Robotics, Intelligent Control and Artificial Intelligence (RICAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2515866431","https://openalex.org/W3105577662","https://openalex.org/W3168407774","https://openalex.org/W3177310631","https://openalex.org/W3202004196","https://openalex.org/W3204835181","https://openalex.org/W4225931058","https://openalex.org/W4294672469","https://openalex.org/W4313002388","https://openalex.org/W4320801574","https://openalex.org/W4386919806"],"related_works":["https://openalex.org/W2121524756","https://openalex.org/W782553550","https://openalex.org/W4379231730","https://openalex.org/W1987967678","https://openalex.org/W4389858081","https://openalex.org/W2633218168","https://openalex.org/W4235897794","https://openalex.org/W2059707233","https://openalex.org/W2095126257","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Infrastructure":[0],"segmentation":[1,91,169],"(bridges,":[2],"dams,":[3],"etc.)":[4],"based":[5,92],"on":[6,93,148,166],"remote":[7,28,44,66],"sensing":[8,29,45,67],"images":[9,68],"has":[10],"been":[11],"widely":[12],"used":[13],"in":[14],"urban":[15],"planning,":[16],"land":[17],"management,":[18],"disaster":[19],"monitoring":[20,23,30],"and":[21,62,110,131,152,160],"other":[22],"fields.":[24],"As":[25],"a":[26,85,111,119,149],"mature":[27],"platform,":[31],"unmanned":[32],"aerial":[33],"vehicles":[34],"(UA":[35],"V)":[36],"have":[37],"become":[38],"the":[39,52,58,73,80,136,153,157,163,167],"main":[40],"source":[41],"of":[42,48,65,75,142,162],"low-altitude":[43],"image":[46],"acquisition":[47],"infrastructures.":[49],"However,":[50],"with":[51],"increasing":[53],"data":[54,60],"acquired":[55],"by":[56],"UAVs,":[57],"large":[59],"volume":[61],"high":[63,158],"resolution":[64],"lead":[69],"to":[70],"challenges":[71],"for":[72,89,134],"task":[74],"infrastructure":[76,90,168],"segmentation.":[77],"To":[78],"solve":[79],"difficulties,":[81],"this":[82,116,143],"paper":[83,117,144],"proposes":[84,118],"deep":[86],"learning":[87],"method":[88,165],"adaptive":[94,106],"hidden":[95],"layer":[96,107],"feature":[97],"fusion,":[98],"which":[99],"specifically":[100],"contains":[101],"an":[102,105],"encoder":[103],"network,":[104],"selection":[108],"mechanism,":[109],"decoder":[112],"network.":[113,139],"In":[114],"addition,":[115],"composite":[120],"loss":[121,130],"function":[122],"containing":[123],"two":[124],"evaluation":[125,129],"metrics,":[126],"namely,":[127],"boundary":[128],"Tversky":[132],"loss,":[133],"training":[135],"proposed":[137,164],"neural":[138],"The":[140],"validation":[141],"is":[145],"carried":[146],"out":[147],"real-world":[150],"dataset,":[151],"experimental":[154],"results":[155],"demonstrate":[156],"accuracy":[159],"reliability":[161],"task.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
