{"id":"https://openalex.org/W4382652489","doi":"https://doi.org/10.1587/transinf.2022edp7149","title":"A Low-Cost Neural ODE with Depthwise Separable Convolution for Edge Domain Adaptation on FPGAs","display_name":"A Low-Cost Neural ODE with Depthwise Separable Convolution for Edge Domain Adaptation on FPGAs","publication_year":2023,"publication_date":"2023-06-30","ids":{"openalex":"https://openalex.org/W4382652489","doi":"https://doi.org/10.1587/transinf.2022edp7149"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2022edp7149","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2022edp7149","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/7/E106.D_2022EDP7149/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/7/E106.D_2022EDP7149/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004530377","display_name":"Hiroki Kawakami","orcid":"https://orcid.org/0009-0007-0515-0445"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki KAWAKAMI","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010867165","display_name":"Hirohisa Watanabe","orcid":"https://orcid.org/0000-0001-8553-8536"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hirohisa WATANABE","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078355355","display_name":"Keisuke Sugiura","orcid":"https://orcid.org/0000-0001-8534-2381"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keisuke SUGIURA","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041549339","display_name":"Hiroki Matsutani","orcid":"https://orcid.org/0000-0001-9578-3842"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki MATSUTANI","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6526,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74378893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"E106.D","issue":"7","first_page":"1186","last_page":"1197"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T12676","display_name":"Machine Learning and ELM","score":0.9979000091552734,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9940000176429749,"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/ode","display_name":"Ode","score":0.8950319290161133},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8148178458213806},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.6982605457305908},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6129205226898193},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5820966958999634},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5678746104240417},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5173141956329346},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5169338583946228},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5022091865539551},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.48572784662246704},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.48261722922325134},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.47132590413093567},{"id":"https://openalex.org/keywords/ordinary-differential-equation","display_name":"Ordinary differential equation","score":0.45427024364471436},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4413917660713196},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43627652525901794},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3768710196018219},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3364490270614624},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.22042208909988403},{"id":"https://openalex.org/keywords/differential-equation","display_name":"Differential equation","score":0.17772501707077026},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10883408784866333},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.07851618528366089},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.07204204797744751}],"concepts":[{"id":"https://openalex.org/C34862557","wikidata":"https://www.wikidata.org/wiki/Q178985","display_name":"Ode","level":2,"score":0.8950319290161133},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8148178458213806},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.6982605457305908},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6129205226898193},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5820966958999634},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5678746104240417},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5173141956329346},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5169338583946228},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5022091865539551},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.48572784662246704},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.48261722922325134},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.47132590413093567},{"id":"https://openalex.org/C51544822","wikidata":"https://www.wikidata.org/wiki/Q465274","display_name":"Ordinary differential equation","level":3,"score":0.45427024364471436},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4413917660713196},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43627652525901794},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3768710196018219},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3364490270614624},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.22042208909988403},{"id":"https://openalex.org/C78045399","wikidata":"https://www.wikidata.org/wiki/Q11214","display_name":"Differential equation","level":2,"score":0.17772501707077026},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10883408784866333},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.07851618528366089},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.07204204797744751},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2022edp7149","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2022edp7149","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/7/E106.D_2022EDP7149/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2022edp7149","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2022edp7149","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/7/E106.D_2022EDP7149/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4382652489.pdf"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1722318740","https://openalex.org/W1882958252","https://openalex.org/W2112796928","https://openalex.org/W2117876524","https://openalex.org/W2194775991","https://openalex.org/W2335728318","https://openalex.org/W2531409750","https://openalex.org/W2593768305","https://openalex.org/W2612445135","https://openalex.org/W2767722847","https://openalex.org/W2776940252","https://openalex.org/W2795155917","https://openalex.org/W2808746463","https://openalex.org/W2887936511","https://openalex.org/W2950865323","https://openalex.org/W2964288524","https://openalex.org/W2976047473","https://openalex.org/W2982083293","https://openalex.org/W3008383986","https://openalex.org/W3130641740","https://openalex.org/W3137525302","https://openalex.org/W3174366215","https://openalex.org/W3201612248","https://openalex.org/W3215673675","https://openalex.org/W4224254956"],"related_works":["https://openalex.org/W3082668976","https://openalex.org/W2517973022","https://openalex.org/W1543121148","https://openalex.org/W1580703421","https://openalex.org/W2618518959","https://openalex.org/W2231364979","https://openalex.org/W4295745414","https://openalex.org/W4382202915","https://openalex.org/W4288093367","https://openalex.org/W2489516236"],"abstract_inverted_index":{"High-performance":[0],"deep":[1],"neural":[2],"network":[3],"(DNN)-based":[4],"systems":[5],"are":[6],"in":[7,10,140],"high":[8,16],"demand":[9],"edge":[11,26],"environments.":[12],"Due":[13],"to":[14,22,90,155,173,193],"its":[15],"computational":[17,32],"complexity,":[18],"it":[19],"is":[20,132,189],"challenging":[21],"deploy":[23],"DNNs":[24],"on":[25,31,134],"devices":[27],"with":[28,99],"strict":[29],"limitations":[30],"resources.":[33],"In":[34],"this":[35],"paper,":[36],"we":[37],"derive":[38],"a":[39,66,91,95,106,156],"compact":[40],"while":[41,179],"highly-accurate":[42],"DNN":[43],"model,":[44],"termed":[45],"dsODENet,":[46,111],"by":[47,191,202],"combining":[48],"recently-proposed":[49],"parameter":[50,182],"reduction":[51],"techniques:":[52],"Neural":[53,63,176],"ODE":[54,64,177],"(Ordinary":[55],"Differential":[56],"Equation)":[57],"and":[58,70,72,116,122,138,151,186],"DSC":[59],"(Depthwise":[60],"Separable":[61],"Convolution).":[62],"exploits":[65],"similarity":[67],"between":[68],"ResNet":[69],"ODE,":[71],"shares":[73],"most":[74],"of":[75,142],"weight":[76],"parameters":[77,115],"among":[78],"multiple":[79],"layers,":[80],"which":[81],"greatly":[82],"reduces":[83],"the":[84,114,180,199],"memory":[85],"consumption.":[86],"We":[87,103],"apply":[88],"dsODENet":[89,163],"domain":[92,143,169],"adaptation":[93,144,170],"as":[94],"practical":[96],"use":[97],"case":[98],"image":[100],"classification":[101],"datasets.":[102],"also":[104],"propose":[105],"resource-efficient":[107],"FPGA-based":[108],"design":[109],"for":[110,120],"where":[112],"all":[113],"feature":[117],"maps":[118],"except":[119],"pre-":[121,185],"post-processing":[123,187],"layers":[124,188],"can":[125],"be":[126],"mapped":[127],"onto":[128],"on-chip":[129],"memories.":[130],"It":[131],"implemented":[133],"Xilinx":[135],"ZCU104":[136],"board":[137],"evaluated":[139],"terms":[141],"accuracy,":[145],"inference":[146,200],"speed,":[147],"FPGA":[148,196],"resource":[149],"utilization,":[150],"speedup":[152],"rate":[153],"compared":[154,172],"software":[157],"counterpart.":[158],"The":[159],"results":[160],"demonstrate":[161],"that":[162],"achieves":[164],"comparable":[165],"or":[166],"slightly":[167],"better":[168],"accuracy":[171],"our":[174],"baseline":[175],"implementation,":[178],"total":[181],"size":[183],"without":[184],"reduced":[190],"54.2%":[192],"79.8%.":[194],"Our":[195],"implementation":[197],"accelerates":[198],"speed":[201],"23.8":[203],"times.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
