{"id":"https://openalex.org/W4378800869","doi":"https://doi.org/10.1145/3583781.3590225","title":"SenTer: A Reconfigurable Processing-in-Sensor Architecture Enabling Efficient Ternary MLP","display_name":"SenTer: A Reconfigurable Processing-in-Sensor Architecture Enabling Efficient Ternary MLP","publication_year":2023,"publication_date":"2023-05-31","ids":{"openalex":"https://openalex.org/W4378800869","doi":"https://doi.org/10.1145/3583781.3590225"},"language":"en","primary_location":{"id":"doi:10.1145/3583781.3590225","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583781.3590225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2023","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/A5014997518","display_name":"Sepehr Tabrizchi","orcid":"https://orcid.org/0000-0001-5105-3450"},"institutions":[{"id":"https://openalex.org/I114395901","display_name":"University of Nebraska\u2013Lincoln","ror":"https://ror.org/043mer456","country_code":"US","type":"education","lineage":["https://openalex.org/I114395901"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sepehr Tabrizchi","raw_affiliation_strings":["University of Nebraska-Lincoln, Lincoln, NE, USA"],"affiliations":[{"raw_affiliation_string":"University of Nebraska-Lincoln, Lincoln, NE, USA","institution_ids":["https://openalex.org/I114395901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057223184","display_name":"Rebati Gaire","orcid":"https://orcid.org/0000-0001-8413-3393"},"institutions":[{"id":"https://openalex.org/I114395901","display_name":"University of Nebraska\u2013Lincoln","ror":"https://ror.org/043mer456","country_code":"US","type":"education","lineage":["https://openalex.org/I114395901"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rebati Gaire","raw_affiliation_strings":["University of Nebraska-Lincoln, Lincoln, NE, USA"],"affiliations":[{"raw_affiliation_string":"University of Nebraska-Lincoln, Lincoln, NE, USA","institution_ids":["https://openalex.org/I114395901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051680668","display_name":"Shaahin Angizi","orcid":"https://orcid.org/0000-0003-2289-6381"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaahin Angizi","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077392159","display_name":"Arman Roohi","orcid":"https://orcid.org/0000-0002-0900-8768"},"institutions":[{"id":"https://openalex.org/I114395901","display_name":"University of Nebraska\u2013Lincoln","ror":"https://ror.org/043mer456","country_code":"US","type":"education","lineage":["https://openalex.org/I114395901"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arman Roohi","raw_affiliation_strings":["University of Nebraska-Lincoln, Lincoln, NE, USA"],"affiliations":[{"raw_affiliation_string":"University of Nebraska-Lincoln, Lincoln, NE, USA","institution_ids":["https://openalex.org/I114395901"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014997518"],"corresponding_institution_ids":["https://openalex.org/I114395901"],"apc_list":null,"apc_paid":null,"fwci":0.4011,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58808197,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"497","last_page":"502"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9998000264167786,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9997000098228455,"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/T11472","display_name":"Analytical Chemistry and Sensors","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1502","display_name":"Bioengineering"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.826471745967865},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.662110447883606},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5230173468589783},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.517419695854187},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.493056982755661},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4657761752605438},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4590948522090912},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.44582027196884155},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4312569200992584},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4108705520629883},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.36901792883872986},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.34116417169570923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2335735261440277},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10155385732650757},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09675341844558716},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09605464339256287}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.826471745967865},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.662110447883606},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5230173468589783},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.517419695854187},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.493056982755661},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4657761752605438},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4590948522090912},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.44582027196884155},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4312569200992584},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4108705520629883},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.36901792883872986},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34116417169570923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2335735261440277},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10155385732650757},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09675341844558716},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09605464339256287},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583781.3590225","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583781.3590225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2023","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8899999856948853,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G3242965485","display_name":null,"funder_award_id":"2216772, 2216773","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2112796928","https://openalex.org/W2511743527","https://openalex.org/W2592539811","https://openalex.org/W3036519573","https://openalex.org/W3048680376","https://openalex.org/W3096649732","https://openalex.org/W3135778105","https://openalex.org/W4312050964","https://openalex.org/W4319069044"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456","https://openalex.org/W2136232598"],"abstract_inverted_index":{"Recently,":[0],"Intelligent":[1],"IoT":[2],"(IIoT),":[3],"including":[4],"various":[5,137],"sensors,":[6],"has":[7],"gained":[8],"significant":[9],"attention":[10],"due":[11],"to":[12,27,106,140],"its":[13,104],"capability":[14],"of":[15,86,115],"sensing,":[16],"deciding,":[17],"and":[18,31,65,78,101,120],"acting":[19],"by":[20,124],"leveraging":[21],"artificial":[22],"neural":[23],"networks":[24],"(ANN).":[25],"Nevertheless,":[26],"achieve":[28],"acceptable":[29,134],"accuracy":[30,135],"high":[32],"performance":[33],"in":[34,63,97],"visual":[35],"systems,":[36],"a":[37,107],"power-delay-efficient":[38],"architecture":[39],"is":[40,84],"required.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45],"propose":[46],"an":[47],"ultra-low-power":[48],"processing":[49],"in-sensor":[50],"architecture,":[51],"namely":[52],"SenTer,":[53],"realizing":[54],"low-precision":[55],"ternary":[56],"multi-layer":[57],"perceptron":[58],"networks,":[59],"which":[60],"can":[61],"operate":[62],"detection":[64],"classification":[66],"modes.":[67],"Moreover,":[68],"SenTer":[69,83,110],"supports":[70],"two":[71],"activation":[72],"functions":[73],"based":[74],"on":[75,136],"user":[76],"needs":[77],"the":[79,89,93,98,113,141],"desired":[80],"accuracy-energy":[81],"trade-off.":[82],"capable":[85],"performing":[87],"all":[88],"required":[90],"computations":[91],"for":[92],"MLP's":[94],"first":[95],"layer":[96],"analog":[99,116],"domain":[100],"then":[102],"submitting":[103],"results":[105,132],"co-processor.":[108],"Therefore,":[109],"significantly":[111],"reduces":[112],"overhead":[114],"buffers,":[117],"data":[118],"conversion,":[119],"transmission":[121],"power":[122],"consumption":[123],"using":[125],"only":[126],"one":[127],"ADC.":[128],"Additionally,":[129],"our":[130],"simulation":[131],"demonstrate":[133],"datasets":[138],"compared":[139],"full":[142],"precision":[143],"models.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}