{"id":"https://openalex.org/W2995929575","doi":"https://doi.org/10.1080/13658816.2019.1698742","title":"Automatic alignment of contemporary vector data and georeferenced historical maps using reinforcement learning","display_name":"Automatic alignment of contemporary vector data and georeferenced historical maps using reinforcement learning","publication_year":2019,"publication_date":"2019-12-09","ids":{"openalex":"https://openalex.org/W2995929575","doi":"https://doi.org/10.1080/13658816.2019.1698742","mag":"2995929575"},"language":"en","primary_location":{"id":"doi:10.1080/13658816.2019.1698742","doi":"https://doi.org/10.1080/13658816.2019.1698742","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2019.1698742","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["dongbi-b","poland-100"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5061358208","display_name":"Weiwei Duan","orcid":"https://orcid.org/0000-0002-7162-5310","observed_orcids":["https://orcid.org/0000-0002-7162-5310"]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Weiwei Duan","raw_affiliation_strings":["Department of Computer Science, University of Southern California, Los Angeles, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045786247","display_name":"Yao\u2010Yi Chiang","orcid":"https://orcid.org/0000-0002-8923-0130","observed_orcids":["https://orcid.org/0000-0002-8923-0130"]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yao-Yi Chiang","raw_affiliation_strings":["Spatial Sciences Institute, University of Southern California, Los Angeles, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Spatial Sciences Institute, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087645671","display_name":"Stefan Leyk","orcid":"https://orcid.org/0000-0001-9180-4853","observed_orcids":["https://orcid.org/0000-0001-9180-4853"]},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stefan Leyk","raw_affiliation_strings":["Department of Geography, University of Colorado Boulder, Boulder, CO, USA"],"raw_orcid":"https://orcid.org/0000-0001-9180-4853","affiliations":[{"raw_affiliation_string":"Department of Geography, University of Colorado Boulder, Boulder, CO, USA","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036895728","display_name":"Johannes Uhl","orcid":"https://orcid.org/0000-0002-4861-5915","observed_orcids":["https://orcid.org/0000-0002-4861-5915"]},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Johannes H. Uhl","raw_affiliation_strings":["Department of Geography, University of Colorado Boulder, Boulder, CO, USA"],"raw_orcid":"https://orcid.org/0000-0002-4861-5915","affiliations":[{"raw_affiliation_string":"Department of Geography, University of Colorado Boulder, Boulder, CO, USA","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089542402","display_name":"Craig A. Knoblock","orcid":"https://orcid.org/0000-0002-6371-4807","observed_orcids":["https://orcid.org/0000-0002-6371-4807"]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Craig A. Knoblock","raw_affiliation_strings":["Information Sciences Institute, University of Southern California, Los Angeles, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Sciences Institute, University of Southern California, Los Angeles, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5061358208"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":1.5847,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.84576747,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"34","issue":"4","first_page":"824","last_page":"849"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.8330000042915344,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.8330000042915344,"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/T13854","display_name":"Historical Geography and Cartography","score":0.10040000081062317,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10757","display_name":"Geographic Information Systems Studies","score":0.03709999844431877,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/historical-maps","display_name":"historical maps","score":0.675000011920929},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"reinforcement learning","score":0.8479999899864197},{"id":"https://openalex.org/keywords/georeferencing","display_name":"georeferencing","score":0.8479999899864197},{"id":"https://openalex.org/keywords/roads","display_name":"roads","score":0.5189999938011169},{"id":"https://openalex.org/keywords/water-lines","display_name":"water lines","score":0.8489999771118164},{"id":"https://openalex.org/keywords/railways","display_name":"railways","score":0.9729999899864197},{"id":"https://openalex.org/keywords/map-archives","display_name":"map archives","score":0.43299999833106995}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6427154541015625},{"id":"https://openalex.org/C181844469","wikidata":"https://www.wikidata.org/wiki/Q182270","display_name":"Raster graphics","level":2,"score":0.5489804744720459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49596819281578064},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4951860010623932},{"id":"https://openalex.org/C41856607","wikidata":"https://www.wikidata.org/wiki/Q483130","display_name":"Geographic information system","level":2,"score":0.48857054114341736},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4714185893535614},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4658105671405792},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4583444595336914},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.41321420669555664},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.33853209018707275},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3311404585838318},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.27661973237991333},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.12898674607276917},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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:10.1080/13658816.2019.1698742","doi":"https://doi.org/10.1080/13658816.2019.1698742","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2019.1698742","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["dongbi-b","poland-100"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W1625553374","https://openalex.org/W1686810756","https://openalex.org/W1977655452","https://openalex.org/W1981276685","https://openalex.org/W2012299618","https://openalex.org/W2027311243","https://openalex.org/W2058207201","https://openalex.org/W2062118960","https://openalex.org/W2097353874","https://openalex.org/W2107726111","https://openalex.org/W2109268594","https://openalex.org/W2121863487","https://openalex.org/W2124351162","https://openalex.org/W2160803144","https://openalex.org/W2163605009","https://openalex.org/W2163771205","https://openalex.org/W2170603638","https://openalex.org/W2263536287","https://openalex.org/W2325929630","https://openalex.org/W2604272474","https://openalex.org/W2736151701","https://openalex.org/W2766875591","https://openalex.org/W2782762915","https://openalex.org/W2794301933","https://openalex.org/W2891211998","https://openalex.org/W2964309882","https://openalex.org/W4214717370","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2768395416","https://openalex.org/W6947393333","https://openalex.org/W2984054586","https://openalex.org/W4411149417","https://openalex.org/W3024456019","https://openalex.org/W7148449454","https://openalex.org/W7197004204","https://openalex.org/W6891770993","https://openalex.org/W4308989641","https://openalex.org/W4415965507"],"abstract_inverted_index":{"With":[0],"large":[1],"amounts":[2],"of":[3,41,62,90,100,113,117,120,143],"digital":[4],"map":[5],"archives":[6],"becoming":[7],"available,":[8],"automatically":[9],"extracting":[10,39,173],"information":[11],"from":[12,44,98],"scanned":[13,45,124,147],"historical":[14,24,67,101,125],"maps":[15,46,68],"is":[16],"needed":[17],"for":[18,38,111,165],"many":[19],"domains":[20],"that":[21,34,184],"require":[22],"long-term":[23],"geographic":[25,42,64,144],"data.":[26],"Convolutional":[27],"Neural":[28],"Networks":[29],"(CNN)":[30],"are":[31,52,94],"powerful":[32],"techniques":[33],"can":[35,57,187],"be":[36,71,108,188],"used":[37,110],"locations":[40,61,116,142],"features":[43,65,119,145,167,192],"if":[47],"sufficient":[48],"representative":[49],"training":[50,75],"data":[51,56,76,93,106],"available.":[53],"Existing":[54],"spatial":[55,87],"provide":[58],"the":[59,79,114,118,123,152,156],"approximate":[60],"corresponding":[63],"in":[66,122],"and":[69,86,196,198],"thus":[70],"useful":[72],"to":[73,139,190],"annotate":[74,140],"automatically.":[77],"However,":[78],"feature":[80,175],"representations,":[81],"publication":[82],"date,":[83],"production":[84],"scales,":[85],"reference":[88],"systems":[89],"contemporary":[91],"vector":[92],"typically":[95],"very":[96],"different":[97],"those":[99],"maps.":[102,126,148],"Hence,":[103],"such":[104,171],"auxiliary":[105],"cannot":[107],"directly":[109],"annotation":[112],"precise":[115,141],"interest":[121],"This":[127,149],"research":[128],"introduces":[129],"an":[130],"automatic":[131],"vector-to-raster":[132],"alignment":[133,153],"algorithm":[134,186],"based":[135],"on":[136,146],"reinforcement":[137,157],"learning":[138,158],"paper":[150],"models":[151],"problem":[154],"using":[155],"framework,":[159],"which":[160],"enables":[161],"informed,":[162],"efficient":[163],"searches":[164],"matching":[166],"without":[168],"pre-processing":[169],"steps,":[170],"as":[172],"specific":[174],"signatures":[176],"(e.g.":[177],"road":[178],"intersections).":[179],"The":[180],"experimental":[181],"results":[182],"show":[183],"our":[185],"applied":[189],"various":[191],"(roads,":[193],"water":[194],"lines,":[195],"railroads)":[197],"achieve":[199],"high":[200],"accuracy.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2019-12-26T00:00:00"}