{"id":"https://openalex.org/W1990315422","doi":"https://doi.org/10.1109/fpl.2009.5272559","title":"CNP: An FPGA-based processor for Convolutional Networks","display_name":"CNP: An FPGA-based processor for Convolutional Networks","publication_year":2009,"publication_date":"2009-08-01","ids":{"openalex":"https://openalex.org/W1990315422","doi":"https://doi.org/10.1109/fpl.2009.5272559","mag":"1990315422"},"language":"en","primary_location":{"id":"doi:10.1109/fpl.2009.5272559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fpl.2009.5272559","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Conference on Field Programmable Logic and Applications","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/A5023316826","display_name":"Cl\u00e9ment Farabet","orcid":null},"institutions":[{"id":"https://openalex.org/I36672615","display_name":"Courant Institute of Mathematical Sciences","ror":"https://ror.org/037tm7f56","country_code":"US","type":"education","lineage":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Clement Farabet","raw_affiliation_strings":["Courant Institute of Mathematical Sciences, New York University, New York, NY, USA","Courant Institute of Mathematical Sciences, New York University, 715 Broadway, 10003, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Courant Institute of Mathematical Sciences, New York University, New York, NY, USA","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"raw_affiliation_string":"Courant Institute of Mathematical Sciences, New York University, 715 Broadway, 10003, USA","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059509083","display_name":"Cyril Poulet","orcid":null},"institutions":[{"id":"https://openalex.org/I36672615","display_name":"Courant Institute of Mathematical Sciences","ror":"https://ror.org/037tm7f56","country_code":"US","type":"education","lineage":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cyril Poulet","raw_affiliation_strings":["Courant Institute of Mathematical Sciences, New York University, New York, NY, USA","Courant Institute of Mathematical Sciences, New York University, 715 Broadway, 10003, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Courant Institute of Mathematical Sciences, New York University, New York, NY, USA","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"raw_affiliation_string":"Courant Institute of Mathematical Sciences, New York University, 715 Broadway, 10003, USA","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034910686","display_name":"Jefferson Y. Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jefferson Y. Han","raw_affiliation_strings":["Perceptive Pixel, Inc., New York, NY, USA","Perceptive Pixel Inc., 111 8th Avenue, New York, 10011, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Perceptive Pixel, Inc., New York, NY, USA","institution_ids":[]},{"raw_affiliation_string":"Perceptive Pixel Inc., 111 8th Avenue, New York, 10011, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001226970","display_name":"Yann LeCun","orcid":null},"institutions":[{"id":"https://openalex.org/I36672615","display_name":"Courant Institute of Mathematical Sciences","ror":"https://ror.org/037tm7f56","country_code":"US","type":"education","lineage":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yann LeCun","raw_affiliation_strings":["Courant Institute of Mathematical Sciences, New York University, New York, NY, USA","Courant Institute of Mathematical Sciences, New York University, 715 Broadway, 10003, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Courant Institute of Mathematical Sciences, New York University, New York, NY, USA","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]},{"raw_affiliation_string":"Courant Institute of Mathematical Sciences, New York University, 715 Broadway, 10003, USA","institution_ids":["https://openalex.org/I36672615","https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.1656,"has_fulltext":false,"cited_by_count":368,"citation_normalized_percentile":{"value":0.97597296,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"32","last_page":"37"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9980999827384949,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9980999827384949,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10036","display_name":"Advanced Neural Network Applications","score":0.994700014591217,"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":0.8268015384674072},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.8187046647071838},{"id":"https://openalex.org/keywords/compiler","display_name":"Compiler","score":0.5902329087257385},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5034272074699402},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4553729295730591},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.4514833092689514},{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.4366393983364105},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.4321841597557068},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39515766501426697},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3594612181186676},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.25249582529067993}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8268015384674072},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.8187046647071838},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.5902329087257385},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5034272074699402},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4553729295730591},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.4514833092689514},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.4366393983364105},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4321841597557068},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39515766501426697},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3594612181186676},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25249582529067993},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fpl.2009.5272559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fpl.2009.5272559","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Conference on Field Programmable Logic and Applications","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.419.9101","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.419.9101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://snowbird.djvuzone.org/2009/abstracts/158.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4099999964237213,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W169539560","https://openalex.org/W178742210","https://openalex.org/W1624854622","https://openalex.org/W1999497791","https://openalex.org/W2105464770","https://openalex.org/W2112796928","https://openalex.org/W2120284346","https://openalex.org/W2127661044","https://openalex.org/W2132131403","https://openalex.org/W2133233905","https://openalex.org/W2139427956","https://openalex.org/W2161969291","https://openalex.org/W2164598857","https://openalex.org/W2164701340","https://openalex.org/W2175582831","https://openalex.org/W2504108613","https://openalex.org/W2616465717","https://openalex.org/W6607276127","https://openalex.org/W6679135890"],"related_works":["https://openalex.org/W2883256816","https://openalex.org/W2171408034","https://openalex.org/W3003320923","https://openalex.org/W2106140982","https://openalex.org/W2152313554","https://openalex.org/W2064303750","https://openalex.org/W4285042611","https://openalex.org/W1967938402","https://openalex.org/W2386041993","https://openalex.org/W1608572506"],"abstract_inverted_index":{"Convolutional":[0],"networks":[1],"(ConvNets)":[2],"are":[3],"biologically":[4],"inspired":[5],"hierarchical":[6],"architectures":[7],"that":[8],"can":[9,164],"be":[10,165],"trained":[11,105],"to":[12,146],"perform":[13],"a":[14,24,48,81,101,104,111,132],"variety":[15],"of":[16,28,45,62,68,103,113,150],"detection,":[17],"recognition":[18],"and":[19,64,89,107,127,175],"segmentation":[20],"tasks.":[21],"ConvNets":[22,46,63],"have":[23],"feed-forward":[25],"architecture":[26],"consisting":[27],"multiple":[29,69],"linear":[30],"convolution":[31],"filters":[32],"interspersed":[33],"with":[34,84],"pointwise":[35],"non-linear":[36],"squashing":[37],"functions.":[38],"This":[39],"paper":[40],"presents":[41],"an":[42,85,147],"efficient":[43],"implementation":[44,57],"on":[47,74,131],"low-end":[49],"DSP-oriented":[50],"field":[51],"programmable":[52],"gate":[53],"array":[54],"(FPGA).":[55],"The":[56,77,162],"exploits":[58],"the":[59,75,116],"inherent":[60],"parallelism":[61],"takes":[65,100,137],"full":[66],"advantage":[67],"hardware":[70],"multiply":[71],"accumulate":[72],"units":[73],"FPGA.":[76],"entire":[78],"system":[79,124],"uses":[80],"single":[82],"FPGA":[83],"external":[86],"memory":[87],"module,":[88],"no":[90],"extra":[91],"parts.":[92],"A":[93,120],"network":[94],"compiler":[95],"software":[96],"was":[97,125],"implemented,":[98],"which":[99,144],"description":[102],"ConvNet":[106,117,121],"compiles":[108],"it":[109],"into":[110],"sequence":[112],"instructions":[114],"for":[115,156,167,173],"Processor":[118],"(CNP).":[119],"face":[122],"detection":[123,130],"implemented":[126],"tested.":[128],"Face":[129],"512":[133],"times":[134,152],"384":[135],"frame":[136],"100":[138],"ms":[139],"(10":[140],"frames":[141],"per":[142,154],"second),":[143],"corresponds":[145],"average":[148],"performance":[149],"3.4":[151],"109connections":[153],"second":[155],"this":[157],"340":[158],"million":[159],"connection":[160],"network.":[161],"design":[163],"used":[166],"low-power,":[168],"lightweight":[169],"embedded":[170],"vision":[171],"systems":[172],"micro-UAVs":[174],"other":[176],"small":[177],"robots.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":23},{"year":2020,"cited_by_count":36},{"year":2019,"cited_by_count":47},{"year":2018,"cited_by_count":56},{"year":2017,"cited_by_count":55},{"year":2016,"cited_by_count":52},{"year":2015,"cited_by_count":16},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":3}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}