{"id":"https://openalex.org/W4312361445","doi":"https://doi.org/10.1109/iscas48785.2022.9937592","title":"A Heterogeneous FPGA-based Accelerator Design for Efficient and Low-cost Point Clouds Deep Learning Inference","display_name":"A Heterogeneous FPGA-based Accelerator Design for Efficient and Low-cost Point Clouds Deep Learning Inference","publication_year":2022,"publication_date":"2022-05-28","ids":{"openalex":"https://openalex.org/W4312361445","doi":"https://doi.org/10.1109/iscas48785.2022.9937592"},"language":"en","primary_location":{"id":"doi:10.1109/iscas48785.2022.9937592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas48785.2022.9937592","pdf_url":null,"source":{"id":"https://openalex.org/S4363604393","display_name":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","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 Symposium on Circuits and Systems (ISCAS)","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/A5073811996","display_name":"Jinling Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinling Xu","raw_affiliation_strings":["Beijing Institute of Technology,China","Beijing Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology,China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043086248","display_name":"Yonggui Wang","orcid":"https://orcid.org/0000-0002-3777-9447"},"institutions":[{"id":"https://openalex.org/I4210144102","display_name":"Wuhu Hit Robot Technology Research Institute","ror":"https://ror.org/049w4dp92","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144102"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonggui Wang","raw_affiliation_strings":["Zhejiang Qianjiang Robot Co,China","Zhejiang Qianjiang Robot Co, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Qianjiang Robot Co,China","institution_ids":["https://openalex.org/I4210144102"]},{"raw_affiliation_string":"Zhejiang Qianjiang Robot Co, China","institution_ids":["https://openalex.org/I4210144102"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028502185","display_name":"Wenbiao Zhouy","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbiao Zhouy","raw_affiliation_strings":["Beijing Institute of Technology,China","Beijing Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology,China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5073811996"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.06,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.30942535,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"32","issue":null,"first_page":"2725","last_page":"2729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9994000196456909,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9994000196456909,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.778832197189331},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7518259286880493},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6932886242866516},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.5985042452812195},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5726845264434814},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5317686200141907},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.5162158608436584},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.48182979226112366},{"id":"https://openalex.org/keywords/floating-point","display_name":"Floating point","score":0.4807995855808258},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.48070722818374634},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.46924686431884766},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.45736178755760193},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42612987756729126},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3524755835533142},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31526559591293335},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.15222176909446716}],"concepts":[{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.778832197189331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7518259286880493},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6932886242866516},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.5985042452812195},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5726845264434814},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5317686200141907},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5162158608436584},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.48182979226112366},{"id":"https://openalex.org/C84211073","wikidata":"https://www.wikidata.org/wiki/Q117879","display_name":"Floating point","level":2,"score":0.4807995855808258},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.48070722818374634},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.46924686431884766},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.45736178755760193},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42612987756729126},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3524755835533142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31526559591293335},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.15222176909446716},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas48785.2022.9937592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas48785.2022.9937592","pdf_url":null,"source":{"id":"https://openalex.org/S4363604393","display_name":"2022 IEEE International Symposium on Circuits and Systems (ISCAS)","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 Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2094756095","https://openalex.org/W2560609797","https://openalex.org/W2945146780","https://openalex.org/W2948410735","https://openalex.org/W2953212265","https://openalex.org/W2963121255","https://openalex.org/W2963231572","https://openalex.org/W2964062501","https://openalex.org/W2980200167","https://openalex.org/W3012494314","https://openalex.org/W3090190135","https://openalex.org/W3111849155","https://openalex.org/W4214755140","https://openalex.org/W6739778489","https://openalex.org/W6763229141","https://openalex.org/W6763422710"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W2355315220","https://openalex.org/W4200391368","https://openalex.org/W1876592433","https://openalex.org/W2083269738","https://openalex.org/W3028347934","https://openalex.org/W2185692674","https://openalex.org/W2518118925","https://openalex.org/W3159273459","https://openalex.org/W2586397364"],"abstract_inverted_index":{"The":[0],"neural":[1],"networks":[2],"on":[3,50],"3D":[4,27],"data":[5,28],"and":[6,29,35,53,75],"applications":[7],"have":[8],"emerged":[9],"in":[10,63],"the":[11,38,64,69,78],"past":[12],"five":[13],"years.":[14],"However,":[15],"there":[16],"are":[17],"only":[18],"a":[19,46],"few":[20],"dedicated":[21],"hardware":[22],"designs":[23],"were":[24],"proposed":[25],"for":[26,37],"algorithms.":[30,43],"Meanwhile,":[31],"they":[32],"lack":[33],"flexibility":[34],"adaptation":[36],"fast":[39],"evolvement":[40],"of":[41,72],"software":[42],"We":[44],"propose":[45],"heterogeneous":[47],"accelerator":[48,65],"design":[49,80],"Xilinx":[51],"Zynq":[52,54],"UltraScale+":[55],"platform.":[56],"An":[57],"innovative":[58],"vector":[59],"pipeline":[60],"is":[61],"designed":[62],"that":[66],"can":[67],"reach":[68],"near":[70],"limitation":[71],"BRAM":[73],"frequency,":[74],"it":[76],"gives":[77],"final":[79],"frequency":[81],"closure":[82],"at":[83],"550MHz":[84],"with":[85],"100%":[86],"DSP":[87],"usage.":[88]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
