{"id":"https://openalex.org/W4312342549","doi":"https://doi.org/10.1109/igarss46834.2022.9883474","title":"An Efficient Approach for Instance Segmentation of Railway Track Sleepers in Low Altitude UAV Images Using Mask R-CNN","display_name":"An Efficient Approach for Instance Segmentation of Railway Track Sleepers in Low Altitude UAV Images Using Mask R-CNN","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4312342549","doi":"https://doi.org/10.1109/igarss46834.2022.9883474"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9883474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883474","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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/A5101479242","display_name":"Arun Kumar Singh","orcid":"https://orcid.org/0000-0001-6176-3966"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Arun Kumar Singh","raw_affiliation_strings":["Department of Electronics and Communication Engineering"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037382541","display_name":"Arun Kant Dwivedi","orcid":"https://orcid.org/0000-0001-7855-0457"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arun Kant Dwivedi","raw_affiliation_strings":["Indian Institute of Technology Roorkee,Department of Computer Science and Engineering,Roorkee,Uttarakhand,India,247667"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Roorkee,Department of Computer Science and Engineering,Roorkee,Uttarakhand,India,247667","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005682027","display_name":"Maram Sumanth","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maram Sumanth","raw_affiliation_strings":["Department of Electronics and Communication Engineering"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075489586","display_name":"Dharmendra Singh","orcid":"https://orcid.org/0000-0002-0396-1494"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dharmendra Singh","raw_affiliation_strings":["Department of Electronics and Communication Engineering"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101479242"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.7118,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.9751938,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4895","last_page":"4898"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10842","display_name":"Railway Engineering and Dynamics","score":0.9919999837875366,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9800999760627747,"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/track","display_name":"Track (disk drive)","score":0.8045639991760254},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7202253341674805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.709624171257019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7078348398208618},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6990289688110352},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6078197956085205},{"id":"https://openalex.org/keywords/ballast","display_name":"Ballast","score":0.5694748163223267},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5118826627731323},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.5037655234336853},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22438526153564453}],"concepts":[{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.8045639991760254},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7202253341674805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.709624171257019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7078348398208618},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6990289688110352},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6078197956085205},{"id":"https://openalex.org/C125907379","wikidata":"https://www.wikidata.org/wiki/Q4851537","display_name":"Ballast","level":2,"score":0.5694748163223267},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5118826627731323},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.5037655234336853},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22438526153564453},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.0},{"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/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/igarss46834.2022.9883474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883474","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W2183182206","https://openalex.org/W2774869152","https://openalex.org/W2806070179","https://openalex.org/W2944165510","https://openalex.org/W2947168367","https://openalex.org/W3039368862","https://openalex.org/W3105054740","https://openalex.org/W3130525189","https://openalex.org/W3133142981","https://openalex.org/W3207553005"],"related_works":["https://openalex.org/W580766000","https://openalex.org/W2152454325","https://openalex.org/W647532056","https://openalex.org/W287043150","https://openalex.org/W4480445","https://openalex.org/W2527199157","https://openalex.org/W4206567838","https://openalex.org/W2364548847","https://openalex.org/W2339143372","https://openalex.org/W628066528"],"abstract_inverted_index":{"Instance":[0],"segmentation":[1,119],"of":[2,35,48],"sleepers":[3,37],"is":[4,41],"essential":[5],"in":[6,38,59,75,108,133],"vision-based":[7,127],"railway":[8,19,49],"track":[9,92,128],"monitoring":[10,129],"to":[11,44,70,88],"ensure":[12],"good":[13],"condition":[14],"and":[15,54,56,120],"enumeration.":[16],"Sleepers":[17],"for":[18,29,125],"tracks":[20],"are":[21,67,123],"critical":[22],"as":[23,26,104],"they":[24],"serve":[25],"the":[27,36,45,72,90,126],"foundation":[28],"all":[30],"other":[31],"auxiliary":[32],"components.":[33],"Segmentation":[34],"UAV":[39,60,132],"images":[40,76,109],"challenging":[42],"due":[43],"complex":[46],"environment":[47],"track,":[50],"occlusion":[51],"by":[52],"rail":[53,91],"ballast":[55],"viewpoint":[57],"variation":[58],"images.":[61],"Region-based":[62],"convolutional":[63],"neural":[64],"networks":[65],"(RCNNs)":[66],"popular":[68],"recently":[69],"segment":[71,89],"distinct":[73],"objects":[74],"based":[77,94],"on":[78,95],"mask":[79],"generation":[80],"methods.":[81],"This":[82],"paper":[83],"applies":[84],"an":[85],"efficient":[86,118],"approach":[87,122],"sleeper":[93],"Mask-Rcnn":[96],"with":[97],"backbone":[98],"ResNet101":[99],"+":[100],"Fpn,":[101],"which":[102],"acts":[103],"a":[105],"feature":[106],"extractor":[107],"captured":[110],"from":[111],"UAV.":[112],"The":[113],"results":[114],"show":[115],"that":[116],"sleeper's":[117],"this":[121],"adaptable":[124],"systems":[130],"using":[131],"real":[134],"scenarios.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}