{"id":"https://openalex.org/W2920272101","doi":"https://doi.org/10.1109/access.2019.2901984","title":"Robust ConvNet Landmark-Based Visual Place Recognition by Optimizing Landmark Matching","display_name":"Robust ConvNet Landmark-Based Visual Place Recognition by Optimizing Landmark Matching","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2920272101","doi":"https://doi.org/10.1109/access.2019.2901984","mag":"2920272101"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2901984","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2901984","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08653820.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08653820.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025698193","display_name":"Yaguang Kong","orcid":"https://orcid.org/0000-0002-0045-3259"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaguang Kong","raw_affiliation_strings":["School of Automation, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100712193","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0002-3545-8199"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["School of Automation, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3545-8199","affiliations":[{"raw_affiliation_string":"School of Automation, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046047163","display_name":"Zhangping Chen","orcid":"https://orcid.org/0000-0002-0749-8441"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangping Chen","raw_affiliation_strings":["School of Automation, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I50760025"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.397,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.63291283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"7","issue":null,"first_page":"30754","last_page":"30767"},"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":0.9995999932289124,"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":0.9995999932289124,"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":0.9994000196456909,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.9895423650741577},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8553370237350464},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8147699236869812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6715010404586792},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5526840090751648},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5185180902481079},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.48886483907699585},{"id":"https://openalex.org/keywords/feature-matching","display_name":"Feature matching","score":0.4752999246120453},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4681651294231415},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.38878458738327026},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07307049632072449},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.07292011380195618}],"concepts":[{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.9895423650741577},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8553370237350464},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8147699236869812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6715010404586792},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5526840090751648},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5185180902481079},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.48886483907699585},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.4752999246120453},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4681651294231415},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.38878458738327026},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07307049632072449},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.07292011380195618},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2901984","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2901984","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08653820.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0748a422f54847589255b22e1519c9d0","is_oa":true,"landing_page_url":"https://doaj.org/article/0748a422f54847589255b22e1519c9d0","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":"IEEE Access, Vol 7, Pp 30754-30767 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2901984","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2901984","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08653820.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2920272101.pdf","grobid_xml":"https://content.openalex.org/works/W2920272101.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W7746136","https://openalex.org/W8177059","https://openalex.org/W301022506","https://openalex.org/W1162411702","https://openalex.org/W1531259569","https://openalex.org/W1532257412","https://openalex.org/W1677409904","https://openalex.org/W1703761565","https://openalex.org/W1749678571","https://openalex.org/W1898304433","https://openalex.org/W2010181071","https://openalex.org/W2012833704","https://openalex.org/W2019336343","https://openalex.org/W2062858132","https://openalex.org/W2079112914","https://openalex.org/W2089497633","https://openalex.org/W2104446196","https://openalex.org/W2109197213","https://openalex.org/W2110405746","https://openalex.org/W2117228865","https://openalex.org/W2118323718","https://openalex.org/W2144824356","https://openalex.org/W2147717514","https://openalex.org/W2150252608","https://openalex.org/W2151103935","https://openalex.org/W2153030800","https://openalex.org/W2163605009","https://openalex.org/W2284029970","https://openalex.org/W2293047233","https://openalex.org/W2317431687","https://openalex.org/W2342383553","https://openalex.org/W2461937780","https://openalex.org/W2565555125","https://openalex.org/W2588764082","https://openalex.org/W2609202703","https://openalex.org/W2630750947","https://openalex.org/W2737165983","https://openalex.org/W2737837382","https://openalex.org/W2757662681","https://openalex.org/W2793301492","https://openalex.org/W2891363375","https://openalex.org/W2894692710","https://openalex.org/W2949513689","https://openalex.org/W3124420883","https://openalex.org/W4230940751","https://openalex.org/W6600313631","https://openalex.org/W6632006871","https://openalex.org/W6653248861","https://openalex.org/W6677953180","https://openalex.org/W6684191040","https://openalex.org/W6699583507"],"related_works":["https://openalex.org/W2350424104","https://openalex.org/W2152949619","https://openalex.org/W1090580760","https://openalex.org/W4365793569","https://openalex.org/W2389991515","https://openalex.org/W2395120299","https://openalex.org/W2499438468","https://openalex.org/W2479744187","https://openalex.org/W2360523411","https://openalex.org/W2172121815"],"abstract_inverted_index":{"Visual":[0],"place":[1],"recognition":[2],"(VPR)":[3],"is":[4],"a":[5,17,22,33],"fundamental":[6],"but":[7],"challenging":[8],"problem":[9],"that":[10,132],"has":[11,156],"not":[12],"been":[13],"solved":[14],"completely":[15],"for":[16,38,84,105],"long":[18],"time,":[19],"especially":[20],"in":[21,87,116],"kaleidoscopic":[23],"environment.":[24],"Recent":[25],"advanced":[26],"works":[27],"which":[28,124],"exploit":[29],"ConvNet":[30,57,141,148,162],"landmarks":[31],"as":[32],"representation":[34],"of":[35,95,139],"an":[36,55],"image":[37,90],"the":[39,88,93,102,107,112,137,146],"VPR":[40,59,143,150],"have":[41],"demonstrated":[42],"promising":[43],"performance":[44],"under":[45],"condition":[46],"and":[47,63,119,144],"viewpoint":[48],"changes.":[49],"In":[50],"this":[51,69],"paper,":[52],"we":[53,75,100],"propose":[54],"improved":[56],"landmark-based":[58,142,163],"with":[60],"better":[61],"robustness":[62,138],"higher":[64,157],"matching":[65],"efficiency":[66,159],"by":[67],"extending":[68],"method":[70,155],"from":[71],"two":[72],"aspects.":[73],"First,":[74],"introduce":[76],"hashing":[77],"to":[78,91],"find":[79],"global":[80],"optimal":[81],"landmark":[82,86,97],"matches":[83,109],"each":[85],"query":[89,118],"boost":[92],"quality":[94],"matched":[96],"pairs.":[98],"Second,":[99],"apply":[101],"sequence":[103],"search":[104],"finding":[106],"best":[108],"basing":[110],"on":[111,126],"temporal":[113],"information":[114],"attached":[115],"both":[117],"reference":[120],"images.":[121],"The":[122],"experiments":[123],"conducted":[125],"four":[127],"challengeable":[128],"benchmark":[129],"datasets":[130],"show":[131],"our":[133,154],"approach":[134],"significantly":[135],"enhances":[136],"traditional":[140],"outperforms":[145],"state-of-the-art":[147],"feature-based":[149],"named":[151],"SeqCNNSLAM.":[152],"Moreover,":[153],"computing":[158],"than":[160],"previous":[161],"VPR.":[164]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
