{"id":"https://openalex.org/W4320024096","doi":"https://doi.org/10.1109/bigdata55660.2022.10020455","title":"Pavement Condition Detection Method Based on Time-Frequency Features and Capsule Neural Network","display_name":"Pavement Condition Detection Method Based on Time-Frequency Features and Capsule Neural Network","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4320024096","doi":"https://doi.org/10.1109/bigdata55660.2022.10020455"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020455","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020455","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"2022 IEEE International Conference on Big Data (Big Data)","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/A5046558187","display_name":"Wanghu Chen","orcid":"https://orcid.org/0000-0002-9233-7609"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wanghu Chen","raw_affiliation_strings":["Northwest Normal University,College of Computer Science and Engineering,Lanzhou,China,730070"],"affiliations":[{"raw_affiliation_string":"Northwest Normal University,College of Computer Science and Engineering,Lanzhou,China,730070","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041718923","display_name":"Pengbo Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengbo Lv","raw_affiliation_strings":["Northwest Normal University,College of Computer Science and Engineering,Lanzhou,China,730070"],"affiliations":[{"raw_affiliation_string":"Northwest Normal University,College of Computer Science and Engineering,Lanzhou,China,730070","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100336938","display_name":"Jing Li","orcid":"https://orcid.org/0000-0002-4770-9311"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["Northwest Normal University,College of Computer Science and Engineering,Lanzhou,China,730070"],"affiliations":[{"raw_affiliation_string":"Northwest Normal University,College of Computer Science and Engineering,Lanzhou,China,730070","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032681127","display_name":"Xiao Ma","orcid":"https://orcid.org/0000-0003-1484-9286"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Ma","raw_affiliation_strings":["Northwest Normal University,College of Computer Science and Engineering,Lanzhou,China,730070"],"affiliations":[{"raw_affiliation_string":"Northwest Normal University,College of Computer Science and Engineering,Lanzhou,China,730070","institution_ids":["https://openalex.org/I68986083"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5046558187"],"corresponding_institution_ids":["https://openalex.org/I68986083"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45178295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4483","last_page":"4490"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9998999834060669,"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":0.9998999834060669,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11220","display_name":"Water Systems and Optimization","score":0.9807000160217285,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.7838338613510132},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7767868041992188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.719177782535553},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5219059586524963},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.476259708404541},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4590931832790375},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4423266649246216},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.41253015398979187},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3801282048225403},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3466186225414276},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1607259213924408}],"concepts":[{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.7838338613510132},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7767868041992188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.719177782535553},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5219059586524963},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.476259708404541},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4590931832790375},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4423266649246216},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.41253015398979187},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3801282048225403},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3466186225414276},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1607259213924408},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020455","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020455","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2966661","https://openalex.org/W1522301498","https://openalex.org/W2007221293","https://openalex.org/W2008059592","https://openalex.org/W2037325199","https://openalex.org/W2047590933","https://openalex.org/W2079224300","https://openalex.org/W2108168925","https://openalex.org/W2128880484","https://openalex.org/W2140208140","https://openalex.org/W2168463792","https://openalex.org/W2185029355","https://openalex.org/W2551393996","https://openalex.org/W2789238015","https://openalex.org/W2790484447","https://openalex.org/W2884423752","https://openalex.org/W2889279447","https://openalex.org/W2944401411","https://openalex.org/W2963384288","https://openalex.org/W2963703618","https://openalex.org/W3021890608","https://openalex.org/W3035571503","https://openalex.org/W3045892765","https://openalex.org/W3088936717","https://openalex.org/W4281480072","https://openalex.org/W6686385793","https://openalex.org/W6743446608"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2087343574","https://openalex.org/W4296209631"],"abstract_inverted_index":{"Pavement":[0],"condition":[1,26,30],"detection":[2,31],"is":[3,33],"beneficial":[4],"to":[5,23,99],"road":[6],"maintenance":[7],"and":[8,20,67,87],"driving":[9],"experience.":[10],"Acceleration":[11],"sensors":[12],"of":[13,40,56,64,71],"smart":[14,41],"phones":[15],"can":[16],"provide":[17],"an":[18,93],"economical":[19],"ubiquitous":[21],"way":[22],"gather":[24],"pavement":[25,29],"data.":[27,73],"A":[28],"method":[32,51,78],"proposed":[34,79],"based":[35],"on":[36],"acceleration":[37],"sensor":[38,72],"data":[39],"phones,":[42],"which":[43],"incorporates":[44],"time-frequency":[45],"features":[46],"into":[47],"capsule":[48],"networks.":[49],"The":[50],"well":[52],"addresses":[53],"the":[54,61,68,77,81,103],"problems":[55],"low":[57],"accuracy":[58],"caused":[59],"by":[60],"length":[62],"change":[63],"time":[65],"series,":[66],"high":[69],"dimensionality":[70],"Experiments":[74],"show":[75],"that":[76],"outperforms":[80],"representative":[82],"methods":[83],"in":[84,95],"accuracy,":[85],"precision":[86],"F1":[88,96],"scores.":[89],"Especially,":[90],"it":[91],"has":[92],"improvement":[94],"score":[97],"up":[98],"31.62%":[100],"compared":[101],"with":[102],"benchmark":[104],"methods.":[105]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
