{"id":"https://openalex.org/W3158723510","doi":"https://doi.org/10.1109/icaiic51459.2021.9415262","title":"Pedestrian Detection System with Edge Computing Integration on Embedded Vehicle","display_name":"Pedestrian Detection System with Edge Computing Integration on Embedded Vehicle","publication_year":2021,"publication_date":"2021-04-13","ids":{"openalex":"https://openalex.org/W3158723510","doi":"https://doi.org/10.1109/icaiic51459.2021.9415262","mag":"3158723510"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic51459.2021.9415262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic51459.2021.9415262","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5064022627","display_name":"Ching-Lung Su","orcid":null},"institutions":[{"id":"https://openalex.org/I75357094","display_name":"National Yunlin University of Science and Technology","ror":"https://ror.org/04qkq2m54","country_code":"TW","type":"education","lineage":["https://openalex.org/I75357094"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ching-Lung Su","raw_affiliation_strings":["National Yunlin University of Science and Technology, Yunlin, Taiwan","National Yunlin University of Science and Technology,Department of Electronic Engineering,Yunlin,Taiwan,64002"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Yunlin University of Science and Technology, Yunlin, Taiwan","institution_ids":["https://openalex.org/I75357094"]},{"raw_affiliation_string":"National Yunlin University of Science and Technology,Department of Electronic Engineering,Yunlin,Taiwan,64002","institution_ids":["https://openalex.org/I75357094"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083357230","display_name":"Wen\u2010Cheng Lai","orcid":"https://orcid.org/0000-0002-8778-9336"},"institutions":[{"id":"https://openalex.org/I75357094","display_name":"National Yunlin University of Science and Technology","ror":"https://ror.org/04qkq2m54","country_code":"TW","type":"education","lineage":["https://openalex.org/I75357094"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wen-Cheng Lai","raw_affiliation_strings":["National Yunlin University of Science and Technology, Yunlin, Taiwan","National Yunlin University of Science and Technology,Department of Electronic Engineering,Yunlin,Taiwan,64002"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Yunlin University of Science and Technology, Yunlin, Taiwan","institution_ids":["https://openalex.org/I75357094"]},{"raw_affiliation_string":"National Yunlin University of Science and Technology,Department of Electronic Engineering,Yunlin,Taiwan,64002","institution_ids":["https://openalex.org/I75357094"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111535027","display_name":"Chun-Te Li","orcid":null},"institutions":[{"id":"https://openalex.org/I75357094","display_name":"National Yunlin University of Science and Technology","ror":"https://ror.org/04qkq2m54","country_code":"TW","type":"education","lineage":["https://openalex.org/I75357094"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chun Te Li","raw_affiliation_strings":["National Yunlin University of Science and Technology, Yunlin, Taiwan","National Yunlin University of Science and Technology,Department of Electronic Engineering,Yunlin,Taiwan,64002"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Yunlin University of Science and Technology, Yunlin, Taiwan","institution_ids":["https://openalex.org/I75357094"]},{"raw_affiliation_string":"National Yunlin University of Science and Technology,Department of Electronic Engineering,Yunlin,Taiwan,64002","institution_ids":["https://openalex.org/I75357094"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2613,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.81634167,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"450","last_page":"453"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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":0.9993000030517578,"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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7651029825210571},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.7053097486495972},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.696159839630127},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5915840864181519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5352039933204651},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4972379505634308},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4859856069087982},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.46608278155326843},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.4552929699420929},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.4364311099052429},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42179393768310547},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3633309304714203},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.356867253780365},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.35542765259742737},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1630505919456482},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10809868574142456}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7651029825210571},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.7053097486495972},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.696159839630127},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5915840864181519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5352039933204651},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4972379505634308},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4859856069087982},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.46608278155326843},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.4552929699420929},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.4364311099052429},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42179393768310547},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3633309304714203},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.356867253780365},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.35542765259742737},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1630505919456482},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10809868574142456},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic51459.2021.9415262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic51459.2021.9415262","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6100000143051147,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2279098554","https://openalex.org/W2302255633","https://openalex.org/W2612445135","https://openalex.org/W2752782242","https://openalex.org/W2963420686","https://openalex.org/W3110131383","https://openalex.org/W4297775537","https://openalex.org/W6695314431","https://openalex.org/W6737664043"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2392615019","https://openalex.org/W2879046444","https://openalex.org/W2791998051","https://openalex.org/W2316461419","https://openalex.org/W2578456052","https://openalex.org/W1795042746","https://openalex.org/W2335751644"],"abstract_inverted_index":{"The":[0,37,115],"article":[1,71],"proposes":[2,72],"pedestrian":[3],"detection":[4],"system":[5,67,112],"with":[6,9,131],"edge":[7],"computing":[8],"multi-network":[10],"integration":[11],"on":[12,113],"embedded":[13,66,111],"vehicle.":[14,114],"When":[15],"camera":[16,128],"of":[17,44,53,59,77,82,95,109,129,133],"lens":[18,130],"design":[19,25,117],"in":[20,64],"machine":[21,30],"learning,":[22],"the":[23,51,56,65,75,80,86,105,110],"proposal":[24],"uses":[26],"AdaBoost,":[27],"support":[28],"vector":[29],"(SVM)":[31],"and":[32,50,55,79,124,135],"convolutional":[33],"neural":[34],"network":[35,87],"(CNN).":[36],"disadvantage":[38],"is":[39],"that":[40],"a":[41,121],"large":[42,57],"number":[43,58,81],"samples":[45],"are":[46],"needed":[47],"for":[48,68],"training,":[49],"amount":[52,76],"operation":[54],"parameters":[60,83],"cannot":[61],"be":[62],"used":[63],"vehicles.":[69],"This":[70],"to":[73,100],"reduce":[74],"computation":[78],"required":[84],"by":[85,88,103],"integrating":[89],"different":[90,96],"optimization":[91],"operations":[92],"between":[93],"networks":[94],"architectures,":[97],"so":[98],"as":[99],"achieve":[101],"prediction":[102],"using":[104],"Renesas":[106],"R-car":[107],"H3":[108],"proposed":[116],"can":[118],"maintain":[119],"above":[120],"certain":[122],"accuracy":[123],"cost":[125],"lower":[126],"than":[127],"sensors":[132],"radar":[134],"lidar.":[136]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
