{"id":"https://openalex.org/W3205069684","doi":"https://doi.org/10.1177/00368504211044228","title":"Deep learning based real-time tourist spots detection and recognition mechanism","display_name":"Deep learning based real-time tourist spots detection and recognition mechanism","publication_year":2021,"publication_date":"2021-07-01","ids":{"openalex":"https://openalex.org/W3205069684","doi":"https://doi.org/10.1177/00368504211044228","mag":"3205069684","pmid":"https://pubmed.ncbi.nlm.nih.gov/34668799","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/10454965"},"language":"en","primary_location":{"id":"doi:10.1177/00368504211044228","doi":"https://doi.org/10.1177/00368504211044228","is_oa":true,"landing_page_url":"https://doi.org/10.1177/00368504211044228","pdf_url":null,"source":{"id":"https://openalex.org/S9683234","display_name":"Science Progress","issn_l":"0036-8504","issn":["0036-8504","2047-7163"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-c","medline","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Science Progress","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1177/00368504211044228","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031223656","display_name":"Yen-Chiu Chen","orcid":"https://orcid.org/0000-0001-8587-461X","observed_orcids":["https://orcid.org/0000-0001-8587-461X"]},"institutions":[{"id":"https://openalex.org/I59460038","display_name":"Chung Hua University","ror":"https://ror.org/01yzz0f51","country_code":"TW","type":"education","lineage":["https://openalex.org/I59460038"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yen-Chiu Chen","raw_affiliation_strings":["Department of Information Management, Chung Hua University, Hsinchu, Taiwan"],"raw_orcid":"https://orcid.org/0000-0001-8587-461X","affiliations":[{"raw_affiliation_string":"Department of Information Management, Chung Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I59460038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101553990","display_name":"Kun-Ming Yu","orcid":"https://orcid.org/0000-0001-8706-3490","observed_orcids":["https://orcid.org/0000-0001-8706-3490"]},"institutions":[{"id":"https://openalex.org/I59460038","display_name":"Chung Hua University","ror":"https://ror.org/01yzz0f51","country_code":"TW","type":"education","lineage":["https://openalex.org/I59460038"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Kun-Ming Yu","raw_affiliation_strings":["Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I59460038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015663698","display_name":"Tzu-Hsiang Kao","orcid":"https://orcid.org/0000-0003-1786-9055","observed_orcids":["https://orcid.org/0000-0003-1786-9055"]},"institutions":[{"id":"https://openalex.org/I59460038","display_name":"Chung Hua University","ror":"https://ror.org/01yzz0f51","country_code":"TW","type":"education","lineage":["https://openalex.org/I59460038"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tzu-Hsiang Kao","raw_affiliation_strings":["Department of Information Management, Chung Hua University, Hsinchu, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-1786-9055","affiliations":[{"raw_affiliation_string":"Department of Information Management, Chung Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I59460038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088485562","display_name":"Hao-Lun Hsieh","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I59460038","display_name":"Chung Hua University","ror":"https://ror.org/01yzz0f51","country_code":"TW","type":"education","lineage":["https://openalex.org/I59460038"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hao-Lun Hsieh","raw_affiliation_strings":["Department of Information Management, Chung Hua University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Management, Chung Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I59460038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5031223656"],"corresponding_institution_ids":["https://openalex.org/I59460038"],"apc_list":{"value":1500,"currency":"USD","value_usd":1500},"apc_paid":{"value":1500,"currency":"USD","value_usd":1500},"fwci":0.9164,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.71291513,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":"104","issue":"3_suppl","first_page":"368504211044228","last_page":"368504211044228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9839000105857849,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9839000105857849,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.0142000000923872,"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/T13674","display_name":"Computer Science and Engineering","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/yolov3","display_name":"YOLOv3","score":0.8519999980926514},{"id":"https://openalex.org/keywords/faster-r-cnn","display_name":"Faster R-CNN","score":0.8960000276565552},{"id":"https://openalex.org/keywords/single-shot-multibox-detector","display_name":"Single Shot MultiBox Detector","score":0.9490000009536743},{"id":"https://openalex.org/keywords/object-detection","display_name":"object detection","score":0.8360000252723694},{"id":"https://openalex.org/keywords/real-time-image-recognition","display_name":"real-time image recognition","score":0.7609999775886536},{"id":"https://openalex.org/keywords/smartphone-camera","display_name":"smartphone camera","score":0.7400000095367432},{"id":"https://openalex.org/keywords/travel-itinerary-planning","display_name":"travel itinerary planning","score":0.8429999947547913},{"id":"https://openalex.org/keywords/tourism-information-retrieval","display_name":"tourism information retrieval","score":0.6949999928474426}],"concepts":[{"id":"https://openalex.org/C18918823","wikidata":"https://www.wikidata.org/wiki/Q49389","display_name":"Tourism","level":2,"score":0.8059538006782532},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6668277978897095},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6181653738021851},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5313684940338135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5031573176383972},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43611517548561096},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4358947277069092},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34020301699638367},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32916173338890076},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3077968955039978},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013624","descriptor_name":"Taiwan","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1177/00368504211044228","doi":"https://doi.org/10.1177/00368504211044228","is_oa":true,"landing_page_url":"https://doi.org/10.1177/00368504211044228","pdf_url":null,"source":{"id":"https://openalex.org/S9683234","display_name":"Science Progress","issn_l":"0036-8504","issn":["0036-8504","2047-7163"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-c","medline","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Science Progress","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:10454965","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10454965","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10454965/pdf/10.1177_00368504211044228.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sci Prog","raw_type":"Text"},{"id":"pmid:34668799","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34668799","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Science progress","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:7c0a5e12f3934c26ad8f08175493e0f5","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/7c0a5e12f3934c26ad8f08175493e0f5","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,"listed_in":[],"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":"Science Progress, Vol 104 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1177/00368504211044228","doi":"https://doi.org/10.1177/00368504211044228","is_oa":true,"landing_page_url":"https://doi.org/10.1177/00368504211044228","pdf_url":null,"source":{"id":"https://openalex.org/S9683234","display_name":"Science Progress","issn_l":"0036-8504","issn":["0036-8504","2047-7163"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-c","medline","norway-1","poland-40","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Science Progress","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G6989428604","display_name":"Research on Deep Learning Edge Computing to Flame Development Detection","funder_award_id":"MOST109-2222-E216-001","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3205069684.pdf","grobid_xml":"https://content.openalex.org/works/W3205069684.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1483870316","https://openalex.org/W2126096326","https://openalex.org/W2193145675","https://openalex.org/W2560311620","https://openalex.org/W2567289819","https://openalex.org/W2754198511","https://openalex.org/W2796347433","https://openalex.org/W2890554472","https://openalex.org/W2922102451","https://openalex.org/W2964632911","https://openalex.org/W2972309292","https://openalex.org/W2997900157","https://openalex.org/W3007489506","https://openalex.org/W3015758410","https://openalex.org/W3016718642","https://openalex.org/W3022690034","https://openalex.org/W3049044894","https://openalex.org/W3106250896","https://openalex.org/W3113929572","https://openalex.org/W3157432688","https://openalex.org/W4205568037"],"related_works":["https://openalex.org/W4388819962","https://openalex.org/W4285792851","https://openalex.org/W7118122100","https://openalex.org/W3143350829","https://openalex.org/W3048069016","https://openalex.org/W3197998709","https://openalex.org/W2756736757","https://openalex.org/W3175304028","https://openalex.org/W2964476645","https://openalex.org/W2952910575"],"abstract_inverted_index":{"More":[0],"and":[1,52,82,121,202,209,251,260,263,277,302,326,337],"more":[2,39,187,300],"information":[3,40,188],"on":[4,73,90],"tourist":[5,44,66,85,102,126,142,155,165,181,191],"spots":[6,86,143,166,192],"is":[7,71,107,122,148,274,299,342],"being":[8],"represented":[9],"as":[10,150],"pictures":[11,26,89,130],"rather":[12],"than":[13,304],"text.":[14],"Consequently,":[15],"tourists":[16,176],"who":[17],"are":[18,256,330],"interested":[19],"in":[20,25,117,144,167],"a":[21,34,101,108,132,139,343],"specific":[22],"attraction":[23,173],"shown":[24],"may":[27],"have":[28],"no":[29],"idea":[30],"how":[31],"to":[32,37,53,124,171,185],"perform":[33],"text":[35],"search":[36],"get":[38],"about":[41,189],"the":[42,47,55,58,96,137,154,172,194,230,234,238,264,288,291,305,308,314],"interesting":[43],"spots.":[45],"In":[46,169],"view":[48],"of":[49,57,84,141,159,284],"this":[50,61,160,180,285],"problem":[51],"enhance":[54],"competitiveness":[56],"tourism":[59],"market,":[60],"research":[62,99,161,286],"proposes":[63],"an":[64,151],"innovative":[65],"spot":[67,103,156,182],"identification":[68,83],"mechanism,":[69],"which":[70,106],"based":[72],"deep":[74,216],"learning-based":[75],"object":[76],"detection":[77,81],"technology,":[78],"for":[79,229,268],"real-time":[80],"by":[87,128,237],"taking":[88,129],"location":[91],"or":[92,224,313],"retrieving":[93],"images":[94],"from":[95,193],"Internet.":[97],"This":[98],"establishes":[100],"recognition":[104,157,174,183,235],"system,":[105],"You":[109,241,292,320],"Only":[110,242,293,321],"Look":[111,243,294,322],"Once":[112,244,295,323],"version":[113,245,296,324],"3":[114,297,325],"model":[115,289],"built":[116],"Tensorflow":[118],"AI":[119],"framework,":[120],"used":[123],"identify":[125,163],"attractions":[127],"with":[131,214,334,347],"smartphone's":[133],"camera.":[134],"To":[135],"verify":[136],"possibility,":[138],"set":[140],"Hsinchu":[145,195],"City,":[146],"Taiwan":[147],"taken":[149],"example.":[152],"Currently,":[153],"system":[158,184],"can":[162,177],"28":[164],"Hsinchu.":[168],"addition":[170],"feature,":[175],"further":[178],"use":[179],"obtain":[186],"77":[190],"City":[196],"Government":[197],"Information":[198],"Open":[199],"Data":[200],"Platform,":[201],"then":[203],"make":[204],"dynamic":[205],"travel":[206],"itinerary":[207],"planning":[208],"Google":[210],"MAP":[211],"navigation.":[212],"Compared":[213],"other":[215],"learning":[217,332,345],"models":[218,239,306],"using":[219,240,290,307],"Faster":[220,247,309,338],"region-convolutional":[221,248,310,339],"neural":[222,249,311,340],"networks":[223,312,341],"Single-Shot":[225,252,315,327],"Multibox":[226,253,316,328],"Detector":[227,254,317,329],"algorithms":[228,255],"same":[231],"data":[232],"set,":[233],"time":[236],"3,":[246],"networks,":[250],"respectively":[257],"4.5,":[258],"5,":[259],"9":[261],"s,":[262],"mean":[265],"average":[266],"precision":[267],"each":[269],"when":[270],"IoU":[271],"=":[272],"0.6":[273],"88.63%,":[275],"85%,":[276],"43.19%,":[278],"respectively.":[279],"The":[280],"performance":[281],"experimental":[282],"results":[283],"show":[287],"algorithm":[298],"efficient":[301,335],"precise":[303,348],"algorithms,":[318],"where":[319],"one-stage":[331],"architectures":[333],"features,":[336],"two-stage":[344],"architecture":[346],"features.":[349]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2021-10-25T00:00:00"}