{"id":"https://openalex.org/W4303968631","doi":"https://doi.org/10.3390/rs14194885","title":"Unifying Deep ConvNet and Semantic Edge Features for Loop Closure Detection","display_name":"Unifying Deep ConvNet and Semantic Edge Features for Loop Closure Detection","publication_year":2022,"publication_date":"2022-09-30","ids":{"openalex":"https://openalex.org/W4303968631","doi":"https://doi.org/10.3390/rs14194885"},"language":"en","primary_location":{"id":"doi:10.3390/rs14194885","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14194885","pdf_url":"https://www.mdpi.com/2072-4292/14/19/4885/pdf?version=1664533626","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/19/4885/pdf?version=1664533626","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000239300","display_name":"Jie Jin","orcid":"https://orcid.org/0000-0002-8166-9915"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Jin","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024440170","display_name":"Jiale Bai","orcid":"https://orcid.org/0000-0002-3962-4748"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiale Bai","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100378208","display_name":"Yan Xu","orcid":"https://orcid.org/0000-0002-0271-044X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Xu","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101586794","display_name":"Jiani Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiani Huang","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100378208"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.3063,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.55234215,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"14","issue":"19","first_page":"4885","last_page":"4885"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991999864578247,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991999864578247,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9837999939918518,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7858483791351318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.719555139541626},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6062895059585571},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5562263131141663},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5333124995231628},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5309625864028931},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.5207064747810364},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.474566251039505},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47275859117507935},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4301230311393738},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.4154508709907532},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32546257972717285}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7858483791351318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.719555139541626},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6062895059585571},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5562263131141663},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5333124995231628},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5309625864028931},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.5207064747810364},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.474566251039505},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47275859117507935},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4301230311393738},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.4154508709907532},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32546257972717285},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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":3,"locations":[{"id":"doi:10.3390/rs14194885","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14194885","pdf_url":"https://www.mdpi.com/2072-4292/14/19/4885/pdf?version=1664533626","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b34284f22c2f4e389f6dca3070824111","is_oa":true,"landing_page_url":"https://doaj.org/article/b34284f22c2f4e389f6dca3070824111","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 19, p 4885 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/19/4885/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14194885","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 14; Issue 19; Pages: 4885","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14194885","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14194885","pdf_url":"https://www.mdpi.com/2072-4292/14/19/4885/pdf?version=1664533626","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[{"id":"https://openalex.org/G3637097306","display_name":null,"funder_award_id":"202234","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G466633179","display_name":null,"funder_award_id":"2021YFC2201902","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4303968631.pdf","grobid_xml":"https://content.openalex.org/works/W4303968631.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W1532257412","https://openalex.org/W1968771169","https://openalex.org/W1982452847","https://openalex.org/W1984309565","https://openalex.org/W1989484209","https://openalex.org/W2114594485","https://openalex.org/W2131846894","https://openalex.org/W2144824356","https://openalex.org/W2147238549","https://openalex.org/W2150066425","https://openalex.org/W2155695215","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2461937780","https://openalex.org/W2620629206","https://openalex.org/W2623510711","https://openalex.org/W2737075200","https://openalex.org/W2766144513","https://openalex.org/W2768573964","https://openalex.org/W2828529635","https://openalex.org/W2884148180","https://openalex.org/W2891010743","https://openalex.org/W2940791172","https://openalex.org/W2963125676","https://openalex.org/W2963163009","https://openalex.org/W2963256208","https://openalex.org/W2963374583","https://openalex.org/W2963588253","https://openalex.org/W2982631194","https://openalex.org/W2990048493","https://openalex.org/W3003768717","https://openalex.org/W3010664781","https://openalex.org/W3041133507","https://openalex.org/W3089904094","https://openalex.org/W3107919704","https://openalex.org/W3124420883","https://openalex.org/W3155277185","https://openalex.org/W3168256178","https://openalex.org/W3183768538","https://openalex.org/W3196725351","https://openalex.org/W4225108957","https://openalex.org/W6683411478"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2103835134","https://openalex.org/W4238802473","https://openalex.org/W2034503175","https://openalex.org/W2130009882","https://openalex.org/W2036755558"],"abstract_inverted_index":{"Loop":[0],"closure":[1,20],"detection":[2,21],"is":[3,34,94,123],"an":[4],"important":[5],"component":[6],"of":[7,84,92,99],"Simultaneous":[8],"Localization":[9],"and":[10,30,48,120],"Mapping":[11],"(SLAM).":[12],"In":[13,36],"this":[14],"paper,":[15],"a":[16,60,74],"novel":[17],"two-branch":[18],"loop":[19],"algorithm":[22],"unifying":[23],"deep":[24,54],"Convolutional":[25],"Neural":[26],"Network":[27],"(ConvNet)":[28],"features":[29,33,51,56],"semantic":[31,49,89,107,114],"edge":[32,50,90,108,115],"proposed.":[35],"detail,":[37],"we":[38],"use":[39],"one":[40],"feature":[41,69,77,109],"extraction":[42],"module":[43,65],"to":[44,59,72,80,112,151],"extract":[45],"both":[46],"ConvNet":[47,55],"simultaneously.":[52],"The":[53],"are":[57],"subjected":[58],"Context":[61],"Feature":[62],"Enhancement":[63],"(CFE)":[64],"in":[66,105],"the":[67,82,87,97,106,126,139],"global":[68,76],"ranking":[70,110],"branch":[71,111],"generate":[73],"representative":[75],"descriptor.":[78],"Concurrently,":[79],"reduce":[81],"interference":[83],"dynamic":[85],"features,":[86],"extracted":[88],"information":[91,122],"landmarks":[93],"encoded":[95],"through":[96],"Vector":[98],"Locally":[100],"Aggregated":[101],"Descriptors":[102],"(VLAD)":[103],"framework":[104],"form":[113],"descriptors.":[116],"Finally,":[117],"semantic,":[118],"visual,":[119],"geometric":[121],"integrated":[124],"by":[125],"similarity":[127],"score":[128],"fusion":[129],"calculation.":[130],"Extensive":[131],"experiments":[132],"on":[133],"six":[134],"public":[135],"datasets":[136],"show":[137],"that":[138],"proposed":[140],"approach":[141],"can":[142],"achieve":[143],"competitive":[144],"recall":[145],"rates":[146],"at":[147],"100%":[148],"precision":[149],"compared":[150],"other":[152],"state-of-the-art":[153],"methods.":[154]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
