{"id":"https://openalex.org/W2894293853","doi":"https://doi.org/10.1109/tetci.2018.2829911","title":"Memristive Fully Convolutional Network: An Accurate Hardware Image-Segmentor in Deep Learning","display_name":"Memristive Fully Convolutional Network: An Accurate Hardware Image-Segmentor in Deep Learning","publication_year":2018,"publication_date":"2018-09-24","ids":{"openalex":"https://openalex.org/W2894293853","doi":"https://doi.org/10.1109/tetci.2018.2829911","mag":"2894293853"},"language":"en","primary_location":{"id":"doi:10.1109/tetci.2018.2829911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2018.2829911","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-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/A5002547378","display_name":"Shiping Wen","orcid":"https://orcid.org/0000-0001-8077-7001"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shiping Wen","raw_affiliation_strings":["School of Automation and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Automation and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015033337","display_name":"Huaqiang Wei","orcid":"https://orcid.org/0000-0002-1590-7612"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaqiang Wei","raw_affiliation_strings":["School of Automation and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Automation and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081245089","display_name":"Zhigang Zeng","orcid":"https://orcid.org/0000-0003-4587-3588"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Zeng","raw_affiliation_strings":["School of Automation and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Automation and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074290686","display_name":"Tingwen Huang","orcid":"https://orcid.org/0000-0001-9610-846X"},"institutions":[{"id":"https://openalex.org/I58152225","display_name":"Texas A&M University at Qatar","ror":"https://ror.org/03vb4dm14","country_code":"QA","type":"education","lineage":["https://openalex.org/I58152225","https://openalex.org/I91045830"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Tingwen Huang","raw_affiliation_strings":["Texas A & M University at Qatar, Doha, Qatar"],"affiliations":[{"raw_affiliation_string":"Texas A & M University at Qatar, Doha, Qatar","institution_ids":["https://openalex.org/I58152225"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002547378"],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":5.3484,"has_fulltext":false,"cited_by_count":68,"citation_normalized_percentile":{"value":0.96213468,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"2","issue":"5","first_page":"324","last_page":"334"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9987000226974487,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7756550908088684},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.6603959202766418},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6444196105003357},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.635853111743927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5580941438674927},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5111141800880432},{"id":"https://openalex.org/keywords/memristor","display_name":"Memristor","score":0.4735102951526642},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.47049689292907715},{"id":"https://openalex.org/keywords/massively-parallel","display_name":"Massively parallel","score":0.4628120958805084},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4290289282798767},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27485424280166626},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.26490360498428345},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.14622053503990173}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7756550908088684},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.6603959202766418},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6444196105003357},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.635853111743927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5580941438674927},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5111141800880432},{"id":"https://openalex.org/C150072547","wikidata":"https://www.wikidata.org/wiki/Q212923","display_name":"Memristor","level":2,"score":0.4735102951526642},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.47049689292907715},{"id":"https://openalex.org/C190475519","wikidata":"https://www.wikidata.org/wiki/Q544384","display_name":"Massively parallel","level":2,"score":0.4628120958805084},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4290289282798767},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27485424280166626},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.26490360498428345},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.14622053503990173},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2018.2829911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2018.2829911","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.44999998807907104,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G3476586388","display_name":null,"funder_award_id":"61673188","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3557088081","display_name":null,"funder_award_id":"61673187","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320332753","display_name":"Qatar National Research Fund","ror":"https://ror.org/01svaqq28"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W1546771929","https://openalex.org/W1563967419","https://openalex.org/W1636374761","https://openalex.org/W1680761968","https://openalex.org/W1782590233","https://openalex.org/W1903029394","https://openalex.org/W1964005749","https://openalex.org/W1964288235","https://openalex.org/W1967491101","https://openalex.org/W1973433558","https://openalex.org/W1999085092","https://openalex.org/W2016922062","https://openalex.org/W2025360228","https://openalex.org/W2027895023","https://openalex.org/W2030336536","https://openalex.org/W2037428031","https://openalex.org/W2040429262","https://openalex.org/W2058582133","https://openalex.org/W2060959274","https://openalex.org/W2092985495","https://openalex.org/W2112181056","https://openalex.org/W2134113654","https://openalex.org/W2151133732","https://openalex.org/W2155954834","https://openalex.org/W2158778629","https://openalex.org/W2161236525","https://openalex.org/W2163605009","https://openalex.org/W2271840356","https://openalex.org/W2293078015","https://openalex.org/W2296478878","https://openalex.org/W2395611524","https://openalex.org/W2508602506","https://openalex.org/W2518281301","https://openalex.org/W2525167219","https://openalex.org/W2530876040","https://openalex.org/W2543212506","https://openalex.org/W2556583623","https://openalex.org/W2561341241","https://openalex.org/W2582083242","https://openalex.org/W2590692683","https://openalex.org/W2618530766","https://openalex.org/W2735482625","https://openalex.org/W2784258779","https://openalex.org/W2952793010","https://openalex.org/W3005426916","https://openalex.org/W4243519499","https://openalex.org/W4254672563","https://openalex.org/W6632360823","https://openalex.org/W6633868855","https://openalex.org/W6637179917","https://openalex.org/W6640054144","https://openalex.org/W6641105355","https://openalex.org/W6641839206","https://openalex.org/W6643346842","https://openalex.org/W6649797076","https://openalex.org/W6658001903","https://openalex.org/W6659810309","https://openalex.org/W6680066735","https://openalex.org/W6681914208","https://openalex.org/W6684191040","https://openalex.org/W6694517276","https://openalex.org/W6697590335","https://openalex.org/W6727553916","https://openalex.org/W6728892627","https://openalex.org/W6729634374","https://openalex.org/W6729890135","https://openalex.org/W6731027267","https://openalex.org/W6741050489","https://openalex.org/W6747281898","https://openalex.org/W6825195337","https://openalex.org/W6836480157"],"related_works":["https://openalex.org/W4229452466","https://openalex.org/W2966276069","https://openalex.org/W2304829496","https://openalex.org/W2358307108","https://openalex.org/W3031124155","https://openalex.org/W2463286374","https://openalex.org/W2052332160","https://openalex.org/W2204001882","https://openalex.org/W190448578","https://openalex.org/W2377121108"],"abstract_inverted_index":{"As":[0],"well":[1],"known,":[2],"fully":[3],"convolutional":[4],"network":[5,57,269],"(FCN)":[6],"becomes":[7],"the":[8,11,30,43,66,91,98,106,110,124,132,140,149,156,162,168,192,196,205,233,240,261,267],"state":[9],"of":[10,34,164,171,204,247,266],"art":[12],"for":[13,23],"semantic":[14],"segmentation":[15],"in":[16,41,115,143,175,188],"deep":[17,24,55],"learning.":[18],"Currently,":[19],"new":[20],"hardware":[21,95],"designs":[22],"learning":[25,56,218],"have":[26,48],"focused":[27],"on":[28],"improving":[29],"speed":[31,271],"and":[32,109,130,264],"parallelism":[33],"processing":[35],"units.":[36],"This":[37,70],"motivates":[38],"memristive":[39,54,78],"solutions,":[40],"which":[42,102],"memory":[44],"units":[45],"(i.e.,":[46],"memristors)":[47],"computing":[49],"capabilities.":[50],"However,":[51,232],"designing":[52],"a":[53,73,127,136],"is":[58,103,120,145,209,223,236,243,257],"challenging,":[59],"since":[60,105],"memristors":[61,172],"work":[62],"very":[63],"differently":[64],"from":[65],"traditional":[67,150],"CMOS":[68],"hardware.":[69],"paper":[71],"proposes":[72],"complete":[74],"solution":[75],"to":[76,86,160,195,226,259,270],"implement":[77],"FCN":[79],"(MFCN).":[80],"Voltage":[81],"selectors":[82],"are":[83,113,173],"firstly":[84],"utilized":[85],"realize":[87],"max-pooling":[88],"layers":[89,265],"with":[90,148,178,211,229,245,250],"detailed":[92],"MFCN":[93,144,187,207,234,268],"deconvolution":[94,107,118,133],"circuit":[96],"by":[97,122,199],"massively":[99],"parallel":[100],"structure,":[101],"effective":[104],"kernel":[108,134],"input":[111],"feature":[112],"similar":[114],"size.":[116],"Then,":[117],"calculation":[119],"realized":[121],"converting":[123,131],"image":[125],"into":[126,135],"column":[128],"matrix":[129,158],"sparse":[137],"matrix.":[138],"Meanwhile,":[139],"convolution":[141],"realization":[142],"also":[146,224],"studied":[147],"sliding":[151],"window":[152],"method":[153],"rather":[154],"than":[155],"large":[157],"theory":[159],"overcome":[161],"shortcoming":[163],"low":[165],"efficiency.":[166],"Moreover,":[167],"conductance":[169],"values":[170],"predetermined":[174],"Tensor":[176],"flow":[177],"ex-situ":[179],"training":[180,235],"method.":[181],"In":[182,254],"other":[183],"words,":[184],"we":[185],"train":[186],"software,":[189],"then":[190],"download":[191],"trained":[193],"parameters":[194,249,263],"simulink":[197],"system":[198],"writing":[200],"memristor.":[201],"The":[202,220],"effectiveness":[203],"designed":[206],"scheme":[208,222],"verified":[210],"improved":[212],"accuracy":[213],"over":[214],"some":[215],"existing":[216],"machine":[217],"methods.":[219],"proposed":[221],"adapt":[225],"LFW":[227],"dataset":[228],"three-classification":[230],"tasks.":[231],"time":[237],"consuming":[238],"as":[239],"computational":[241],"burden":[242],"heavy":[244],"thousands":[246],"weight":[248,262],"just":[251],"six":[252],"layers.":[253],"future,":[255],"it":[256],"necessary":[258],"sparsify":[260],"up":[272],"computing.":[273]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}