{"id":"https://openalex.org/W3122795696","doi":"https://doi.org/10.1109/ojcas.2020.3043737","title":"An Energy Efficient EdgeAI Autoencoder Accelerator for Reinforcement Learning","display_name":"An Energy Efficient EdgeAI Autoencoder Accelerator for Reinforcement Learning","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3122795696","doi":"https://doi.org/10.1109/ojcas.2020.3043737","mag":"3122795696"},"language":"en","primary_location":{"id":"doi:10.1109/ojcas.2020.3043737","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2020.3043737","pdf_url":"https://ieeexplore.ieee.org/ielx7/8784029/9314963/09335309.pdf","source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Open Journal of Circuits and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/8784029/9314963/09335309.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Nitheesh Kumar Manjunath","orcid":"https://orcid.org/0000-0001-5551-2124"},"institutions":[{"id":"https://openalex.org/I126744593","display_name":"University of Maryland, Baltimore","ror":"https://ror.org/04rq5mt64","country_code":"US","type":"education","lineage":["https://openalex.org/I126744593"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nitheesh Kumar Manjunath","raw_affiliation_strings":["University of Maryland, Baltimore, MD, USA"],"raw_orcid":"https://orcid.org/0000-0001-5551-2124","affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore, MD, USA","institution_ids":["https://openalex.org/I126744593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067589584","display_name":"Aidin Shiri","orcid":"https://orcid.org/0000-0001-5402-0988"},"institutions":[{"id":"https://openalex.org/I126744593","display_name":"University of Maryland, Baltimore","ror":"https://ror.org/04rq5mt64","country_code":"US","type":"education","lineage":["https://openalex.org/I126744593"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aidin Shiri","raw_affiliation_strings":["University of Maryland, Baltimore, MD, USA"],"raw_orcid":"https://orcid.org/0000-0001-5402-0988","affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore, MD, USA","institution_ids":["https://openalex.org/I126744593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101892993","display_name":"Morteza Hosseini","orcid":"https://orcid.org/0000-0002-7218-7754"},"institutions":[{"id":"https://openalex.org/I126744593","display_name":"University of Maryland, Baltimore","ror":"https://ror.org/04rq5mt64","country_code":"US","type":"education","lineage":["https://openalex.org/I126744593"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Morteza Hosseini","raw_affiliation_strings":["University of Maryland, Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore, MD, USA","institution_ids":["https://openalex.org/I126744593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079352628","display_name":"Bharat Prakash","orcid":null},"institutions":[{"id":"https://openalex.org/I126744593","display_name":"University of Maryland, Baltimore","ror":"https://ror.org/04rq5mt64","country_code":"US","type":"education","lineage":["https://openalex.org/I126744593"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bharat Prakash","raw_affiliation_strings":["University of Maryland, Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore, MD, USA","institution_ids":["https://openalex.org/I126744593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079459509","display_name":"Nicholas R. Waytowich","orcid":"https://orcid.org/0000-0002-3786-0675"},"institutions":[{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas R. Waytowich","raw_affiliation_strings":["U.S. Army Research Laboratory, Aberdeen, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"U.S. Army Research Laboratory, Aberdeen, MD, USA","institution_ids":["https://openalex.org/I166416128"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084010501","display_name":"Tinoosh Mohsenin","orcid":"https://orcid.org/0000-0001-5551-2124"},"institutions":[{"id":"https://openalex.org/I126744593","display_name":"University of Maryland, Baltimore","ror":"https://ror.org/04rq5mt64","country_code":"US","type":"education","lineage":["https://openalex.org/I126744593"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tinoosh Mohsenin","raw_affiliation_strings":["University of Maryland, Baltimore, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore, MD, USA","institution_ids":["https://openalex.org/I126744593"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1750,"currency":"USD","value_usd":1750},"apc_paid":{"value":1750,"currency":"USD","value_usd":1750},"fwci":1.5629,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.85497112,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"2","issue":null,"first_page":"182","last_page":"195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9943000078201294,"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":0.9932000041007996,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8843808174133301},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8247277140617371},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7902754545211792},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5867383480072021},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5348628163337708},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5069010853767395},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.45076996088027954},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.44620364904403687},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42096033692359924},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4204102158546448},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37321656942367554},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.1016569435596466}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8843808174133301},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8247277140617371},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7902754545211792},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5867383480072021},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5348628163337708},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5069010853767395},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.45076996088027954},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.44620364904403687},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42096033692359924},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4204102158546448},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37321656942367554},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.1016569435596466}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ojcas.2020.3043737","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2020.3043737","pdf_url":"https://ieeexplore.ieee.org/ielx7/8784029/9314963/09335309.pdf","source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Open Journal of Circuits and Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:07ff7d91b0764d1fac43a58fabeacddc","is_oa":true,"landing_page_url":"https://doaj.org/article/07ff7d91b0764d1fac43a58fabeacddc","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Open Journal of Circuits and Systems, Vol 2, Pp 182-195 (2021)","raw_type":"article"},{"id":"pmh:oai:mdsoar.org:11603/21047","is_oa":true,"landing_page_url":"http://hdl.handle.net/11603/21047","pdf_url":null,"source":{"id":"https://openalex.org/S4306402556","display_name":"Maryland Shared Open Access Repository (USMAI Consortium)","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":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"doi:10.13016/m2xm9a-tgo3","is_oa":true,"landing_page_url":"https://doi.org/10.13016/m2xm9a-tgo3","pdf_url":null,"source":{"id":"https://openalex.org/S4306402644","display_name":"Digital Repository at the University of Maryland (University of Maryland College Park)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Collection"}],"best_oa_location":{"id":"doi:10.1109/ojcas.2020.3043737","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2020.3043737","pdf_url":"https://ieeexplore.ieee.org/ielx7/8784029/9314963/09335309.pdf","source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Open Journal of Circuits and Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1024130705","display_name":null,"funder_award_id":"W911-NF-10-2-0022","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"},{"id":"https://openalex.org/G5259331294","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"}],"funders":[{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3122795696.pdf","grobid_xml":"https://content.openalex.org/works/W3122795696.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1492347181","https://openalex.org/W1681299129","https://openalex.org/W1902934009","https://openalex.org/W1949804828","https://openalex.org/W2094756095","https://openalex.org/W2108189051","https://openalex.org/W2121863487","https://openalex.org/W2139053308","https://openalex.org/W2145339207","https://openalex.org/W2194775991","https://openalex.org/W2267635276","https://openalex.org/W2405920868","https://openalex.org/W2510850936","https://openalex.org/W2534269850","https://openalex.org/W2543312069","https://openalex.org/W2560017826","https://openalex.org/W2593493485","https://openalex.org/W2614143469","https://openalex.org/W2617317556","https://openalex.org/W2762597430","https://openalex.org/W2766447205","https://openalex.org/W2795256832","https://openalex.org/W2909929243","https://openalex.org/W2922747391","https://openalex.org/W2924168890","https://openalex.org/W2946691598","https://openalex.org/W2952629144","https://openalex.org/W2962887844","https://openalex.org/W2962939807","https://openalex.org/W2963114950","https://openalex.org/W2963424132","https://openalex.org/W2963526839","https://openalex.org/W2968983352","https://openalex.org/W2977485436","https://openalex.org/W2980002279","https://openalex.org/W3011509423","https://openalex.org/W3013550173","https://openalex.org/W3030981716","https://openalex.org/W3036079062","https://openalex.org/W3041764860","https://openalex.org/W3083734093","https://openalex.org/W3100789280","https://openalex.org/W3104395752","https://openalex.org/W3108766273","https://openalex.org/W3147050786","https://openalex.org/W4243934889","https://openalex.org/W4287587695","https://openalex.org/W4294567867","https://openalex.org/W4295262505","https://openalex.org/W6639703010","https://openalex.org/W6655666423","https://openalex.org/W6693397755","https://openalex.org/W6728925229","https://openalex.org/W6775354534","https://openalex.org/W6786416087","https://openalex.org/W6793034496"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W2597809628","https://openalex.org/W4281847915"],"abstract_inverted_index":{"In":[0,100],"EdgeAI":[1,315],"embedded":[2,316],"devices":[3],"that":[4,140],"exploit":[5],"reinforcement":[6],"learning":[7,31,45,74,112],"(RL),":[8],"it":[9],"is":[10,289,340,357,398],"essential":[11],"to":[12,49,84,89,130,226,248,253,264,269,304,342,373,383],"reduce":[13],"the":[14,20,23,28,43,50,55,67,72,85,90,93,97,110,118,132,138,168,182,220,237,242,259,270,294,306,370,384,387,392],"number":[15,295],"of":[16,114,120,167,184,207,293,296,346,379,386],"actions":[17],"taken":[18],"by":[19,53,245,278],"agent":[21,116,143],"in":[22,92,164,187,256,291,361],"real":[24],"world":[25],"and":[26,81,96,127,149,158,171,195,213,230,250,282,300,310,359,376,400,411],"minimize":[27],"compute-intensive":[29],"policies":[30],"process.":[32],"Convolutional":[33],"autoencoders":[34],"(AEs)":[35],"has":[36],"demonstrated":[37],"great":[38],"improvement":[39],"for":[40,65,107,314],"speeding":[41,108],"up":[42,109,263],"policy":[44,73,111,139],"time":[46],"when":[47],"attached":[48],"RL":[51,68,115,142,189],"agent,":[52],"compressing":[54],"high":[56,133],"dimensional":[57],"input":[58],"data":[59,302],"into":[60,156],"a":[61,78,105,284],"small":[62],"latent":[63],"representation":[64],"feeding":[66],"agent.":[69],"Despite":[70],"reducing":[71,241],"time,":[75],"AE":[76,121],"adds":[77],"significant":[79,165],"computational":[80],"memory":[82,172,301],"complexity":[83,134],"model":[86,98,106,169,186,239,243,276],"which":[87,124,162,199,288,367],"contributes":[88],"increase":[91],"total":[94],"computation":[95],"size.":[99],"this":[101],"article,":[102],"we":[103],"propose":[104],"process":[113],"with":[117,204],"use":[119],"neural":[122],"networks,":[123],"engages":[125],"binary":[126],"ternary":[128],"precision":[129],"address":[131],"overhead":[135],"without":[136],"deteriorating":[137],"an":[141,344],"learns.":[144],"Binary":[145],"Neural":[146,151],"Networks":[147,152],"(BNNs)":[148],"Ternary":[150],"(TNNs)":[153],"compress":[154],"weights":[155],"1":[157,348],"2":[159],"bits":[160],"representations,":[161],"result":[163],"compression":[166],"size":[170,244,277],"as":[173,175,236],"well":[174],"simplifying":[176],"multiply-accumulate":[177],"(MAC)":[178],"operations.":[179],"We":[180,280],"evaluate":[181],"performance":[183,235],"our":[185,396],"three":[188],"environments":[190],"including":[191],"DonkeyCar,":[192],"Miniworld":[193,196],"sidewalk,":[194],"Object":[197],"Pickup,":[198],"emulate":[200],"various":[201],"real-world":[202],"applications":[203],"different":[205],"levels":[206],"complexity.":[208],"With":[209],"proper":[210],"hyperparameter":[211],"optimization":[212],"architecture":[214],"exploration,":[215],"TNN":[216,389],"models":[217,258],"achieve":[218,305],"near":[219],"same":[221,393],"average":[222,260],"reward,":[223],"Peak":[224],"Signal":[225],"Noise":[227],"Ratio":[228],"(PSNR)":[229],"Mean":[231],"Squared":[232],"Error":[233],"(MSE)":[234],"full-precision":[238,249,271],"while":[240,329],"10x":[246],"compared":[247,252,268],"3x":[251],"BNNs.":[254],"However,":[255],"BNN":[257],"reward":[261],"drops":[262],"12%":[265],"-":[266],"25%":[267],"even":[272],"after":[273],"increasing":[274],"its":[275],"4x.":[279],"designed":[281],"implemented":[283,321],"scalable":[285],"hardware":[286,320,339,355,397],"accelerator":[287,356],"configurable":[290,341],"terms":[292],"processing":[297],"elements":[298],"(PEs)":[299],"width":[303],"best":[307],"power,":[308],"performance,":[309],"energy":[311,328,407],"efficiency":[312,345],"trade-off":[313],"devices.":[317],"The":[318,338,353],"proposed":[319,354],"on":[322,350,391,409],"Artix-7":[323],"FPGA":[324,351,410],"dissipates":[325],"250":[326],"\u03bcJ":[327,375],"meeting":[330],"30":[331],"frames":[332],"per":[333],"second":[334],"(FPS)":[335],"throughput":[336,378],"requirements.":[337],"reach":[343],"over":[347],"TOP/J":[349],"implementation.":[352],"synthesized":[358],"placed-and-routed":[360],"14":[362],"nm":[363],"FinFET":[364],"ASIC":[365],"technology":[366,404],"brings":[368],"down":[369],"power":[371],"dissipation":[372],"3.9":[374],"maximum":[377],"1,250":[380],"FPS.":[381],"Compared":[382],"state":[385],"art":[388],"implementations":[390],"target":[394],"platform,":[395],"5x":[399],"4.4x":[401],"(2.2x":[402],"if":[403],"scaled)":[405],"more":[406],"efficient":[408],"ASIC,":[412],"respectively.":[413]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
