{"id":"https://openalex.org/W2904430334","doi":"https://doi.org/10.1109/fpl.2018.00092","title":"ADAS and Video Surveillance Analytics System Using Deep Learning Algorithms on FPGA","display_name":"ADAS and Video Surveillance Analytics System Using Deep Learning Algorithms on FPGA","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2904430334","doi":"https://doi.org/10.1109/fpl.2018.00092","mag":"2904430334"},"language":"en","primary_location":{"id":"doi:10.1109/fpl.2018.00092","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fpl.2018.00092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 28th International Conference on Field Programmable Logic and Applications (FPL)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5009175141","display_name":"Yi Shan","orcid":"https://orcid.org/0000-0003-2646-8835"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yi Shan","raw_affiliation_strings":["DeePhi, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeePhi, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5009175141"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.5547999739646912,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.5547999739646912,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.47679999470710754,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.780800461769104},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.6601978540420532},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.6583259105682373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47652944922447205},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.442003458738327},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4133256673812866},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3491544723510742},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3489378094673157},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3284696936607361},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.2717595100402832},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.19075873494148254},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.1373235583305359}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.780800461769104},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.6601978540420532},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.6583259105682373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47652944922447205},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.442003458738327},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4133256673812866},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3491544723510742},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3489378094673157},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3284696936607361},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2717595100402832},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.19075873494148254},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.1373235583305359}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fpl.2018.00092","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fpl.2018.00092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 28th International Conference on Field Programmable Logic and Applications (FPL)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8999999761581421,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W4200391368","https://openalex.org/W2355315220","https://openalex.org/W2210979487","https://openalex.org/W2074043759","https://openalex.org/W2373535795","https://openalex.org/W2082487009","https://openalex.org/W2062940763","https://openalex.org/W2937343495","https://openalex.org/W4360833258"],"abstract_inverted_index":{"Deep":[0],"learning":[1,68,132],"algorithms,":[2],"such":[3],"as":[4],"CNN":[5,42],"(Convolutional":[6],"Neural":[7],"Network),":[8],"could":[9,77,92],"provide":[10],"high":[11],"accuracy":[12],"for":[13,108,125,139],"great":[14],"number":[15],"of":[16,81,88,142],"applications":[17],"including":[18,160],"ADAS":[19,106],"(Advanced":[20],"Driver":[21],"Assistance":[22],"System)":[23],"and":[24,31,55,60,112,116,119,128,137,156],"video":[25,62,84,122],"surveillance":[26,123],"analytics.":[27],"Considering":[28],"processing":[29],"speed":[30,59],"energy":[32],"efficiency,":[33],"FPGA":[34,150,162],"is":[35,152],"a":[36,57,99],"good":[37],"hardware":[38,53],"to":[39,50],"construct":[40],"customized":[41],"solution.":[43],"In":[44],"this":[45,102,161],"demo":[46],"session,":[47],"we":[48],"want":[49],"benefit":[51],"from":[52],"technology,":[54],"show":[56],"fast":[58],"accurate":[61],"analytics":[63],"system":[64,76,107,124],"using":[65],"state-of-the-art":[66,147],"deep":[67,131],"algorithms":[69,133],"running":[70],"on":[71],"low":[72],"power":[73],"FPGA.":[74],"This":[75],"process":[78],"16":[79],"channels":[80],"continuous":[82],"input":[83],"with":[85,168],"the":[86,120,157],"resolution":[87],"1080p.":[89],"Two":[90],"functionalities":[91],"be":[93],"easily":[94],"switched":[95],"by":[96],"just":[97],"clicking":[98],"button":[100],"in":[101],"live":[103],"demo:":[104],"one":[105],"vehicle,":[109,111],"non-motorized":[110],"pedestrian":[113],"detection,":[114,144],"tracking,":[115],"attributes":[117],"analytics;":[118],"other":[121],"face":[126],"detection":[127],"recognition.":[129],"The":[130,149],"used":[134,151],"are":[135],"SSD":[136],"densebox":[138],"two":[140],"kinds":[141],"objects'":[143],"which":[145],"have":[146],"accuracy.":[148],"Xilinx":[153],"MPSoC":[154],"ZU9,":[155],"whole":[158],"board":[159],"only":[163],"cost":[164],"about":[165],"50":[166],"Watts":[167],"Peak":[169],"performance":[170],"at":[171],"5.6":[172],"TOPS.":[173]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
