{"id":"https://openalex.org/W2943279417","doi":"https://doi.org/10.1109/iscas.2019.8702185","title":"Live Demonstration: Bringing Powerful Deep Learning into Daily-Life Devices (Mobiles and FPGAs) Via Deep k-Means","display_name":"Live Demonstration: Bringing Powerful Deep Learning into Daily-Life Devices (Mobiles and FPGAs) Via Deep k-Means","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2943279417","doi":"https://doi.org/10.1109/iscas.2019.8702185","mag":"2943279417"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2019.8702185","is_oa":true,"landing_page_url":"https://doi.org/10.1109/iscas.2019.8702185","pdf_url":"https://ieeexplore.ieee.org/ielx7/8682239/8702066/08702185.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/8682239/8702066/08702185.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100600606","display_name":"Pengfei Xu","orcid":"https://orcid.org/0000-0003-1067-3607"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pengfei Xu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rice University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rice University","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100372089","display_name":"Yue Wang","orcid":"https://orcid.org/0000-0003-0146-7262"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rice University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rice University","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107593559","display_name":"Yang Zhao","orcid":"https://orcid.org/0000-0001-8023-1551"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Zhao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rice University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rice University","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019582323","display_name":"Yingyan Lin","orcid":"https://orcid.org/0000-0001-5946-203X"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingyan Lin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rice University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rice University","institution_ids":["https://openalex.org/I74775410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74775410"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02666842,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9993000030517578,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9972000122070312,"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":0.7602578401565552},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.735541820526123},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.7079710960388184},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7031604647636414},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.6483939290046692},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6436134576797485},{"id":"https://openalex.org/keywords/data-redundancy","display_name":"Data redundancy","score":0.6058156490325928},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5627099275588989},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5134997963905334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49732187390327454},{"id":"https://openalex.org/keywords/auxiliary-memory","display_name":"Auxiliary memory","score":0.45801061391830444},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.45301535725593567},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.43039143085479736},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.422887921333313},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4224892854690552},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3226749897003174},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.25485363602638245},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.1975809931755066},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.14274165034294128},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.12367114424705505},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09596672654151917}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7602578401565552},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.735541820526123},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.7079710960388184},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7031604647636414},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6483939290046692},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6436134576797485},{"id":"https://openalex.org/C7545210","wikidata":"https://www.wikidata.org/wiki/Q838123","display_name":"Data redundancy","level":2,"score":0.6058156490325928},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5627099275588989},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5134997963905334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49732187390327454},{"id":"https://openalex.org/C82687282","wikidata":"https://www.wikidata.org/wiki/Q66221","display_name":"Auxiliary memory","level":2,"score":0.45801061391830444},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.45301535725593567},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.43039143085479736},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.422887921333313},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4224892854690552},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3226749897003174},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.25485363602638245},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.1975809931755066},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.14274165034294128},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.12367114424705505},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09596672654151917},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas.2019.8702185","is_oa":true,"landing_page_url":"https://doi.org/10.1109/iscas.2019.8702185","pdf_url":"https://ieeexplore.ieee.org/ielx7/8682239/8702066/08702185.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/iscas.2019.8702185","is_oa":true,"landing_page_url":"https://doi.org/10.1109/iscas.2019.8702185","pdf_url":"https://ieeexplore.ieee.org/ielx7/8682239/8702066/08702185.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2943279417.pdf","grobid_xml":"https://content.openalex.org/works/W2943279417.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2804193803","https://openalex.org/W4293584584","https://openalex.org/W6639102338","https://openalex.org/W6750227808","https://openalex.org/W6751769266"],"related_works":["https://openalex.org/W2002428578","https://openalex.org/W2897258045","https://openalex.org/W2018406690","https://openalex.org/W2072332896","https://openalex.org/W2951748633","https://openalex.org/W2057691131","https://openalex.org/W2542042335","https://openalex.org/W2952039693","https://openalex.org/W4280621979","https://openalex.org/W4292309272"],"abstract_inverted_index":{"The":[0,19],"record-breaking":[1],"success":[2],"of":[3,12,16,34,57,70,90],"convolutional":[4],"neural":[5],"networks":[6],"(CNNs)":[7],"comes":[8],"at":[9],"the":[10,31,55,71,88],"cost":[11],"a":[13,58],"large":[14],"amount":[15],"model":[17],"parameters.":[18],"resulting":[20],"prohibitive":[21],"memory":[22,78],"storage":[23,45,79],"and":[24,47,80,83,103],"data":[25,81],"movement":[26],"energy":[27],"have":[28,43],"been":[29],"limiting":[30],"extensive":[32],"deployment":[33],"deep":[35,65],"learning":[36],"on":[37],"daily-life":[38,99],"edge":[39],"devices":[40,100],"which":[41,67],"usually":[42],"limited":[44],"capability":[46],"are":[48],"battery-powered.":[49],"To":[50],"this":[51],"end,":[52],"we":[53],"explore":[54],"employment":[56],"recently":[59],"published":[60],"weight":[61],"clustering":[62],"technique,":[63],"called":[64],"k-Means":[66],"makes":[68],"use":[69],"redundancy":[72],"within":[73],"CNN":[74],"parameters":[75],"for":[76],"reduced":[77],"movement,":[82],"demonstrate":[84],"k-Means's":[85],"effectiveness":[86],"in":[87],"context":[89],"an":[91],"interactive":[92],"real-time":[93],"object":[94],"detection":[95],"using":[96],"three":[97],"representative":[98],"(iPhone,":[101],"iPad":[102],"FPGA).":[104]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
