{"id":"https://openalex.org/W4309995345","doi":"https://doi.org/10.1109/ictc55196.2022.9953031","title":"Lazy Net: Lazy Entry Neural Networks for Accelerated and Efficient Inference","display_name":"Lazy Net: Lazy Entry Neural Networks for Accelerated and Efficient Inference","publication_year":2022,"publication_date":"2022-10-19","ids":{"openalex":"https://openalex.org/W4309995345","doi":"https://doi.org/10.1109/ictc55196.2022.9953031"},"language":"en","primary_location":{"id":"doi:10.1109/ictc55196.2022.9953031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc55196.2022.9953031","pdf_url":null,"source":{"id":"https://openalex.org/S4363607740","display_name":"2022 13th International Conference on Information and Communication Technology Convergence (ICTC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 13th International Conference on Information and Communication Technology Convergence (ICTC)","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/A5100695869","display_name":"Junyong Park","orcid":"https://orcid.org/0000-0001-9583-390X"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Junyong Park","raw_affiliation_strings":["Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute(ETRI),Daejeon,Korea","Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute(ETRI), Daejeon, Korea"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute(ETRI),Daejeon,Korea","institution_ids":["https://openalex.org/I142401562"]},{"raw_affiliation_string":"Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute(ETRI), Daejeon, Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412744","display_name":"Daeyoung Kim","orcid":"https://orcid.org/0000-0003-4901-3075"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dae-Young Kim","raw_affiliation_strings":["School of Computing Korea Advanced Institute of Science and Technology(KAIST),Data Engineering and Analysis Lab,Daejeon,Korea","Data Engineering and Analysis Lab, School of Computing Korea Advanced Institute of Science and Technology(KAIST), Daejeon, Korea"],"affiliations":[{"raw_affiliation_string":"School of Computing Korea Advanced Institute of Science and Technology(KAIST),Data Engineering and Analysis Lab,Daejeon,Korea","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"Data Engineering and Analysis Lab, School of Computing Korea Advanced Institute of Science and Technology(KAIST), Daejeon, Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063300693","display_name":"Yong-Hyuk Moon","orcid":"https://orcid.org/0000-0002-6700-1070"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]},{"id":"https://openalex.org/I88761825","display_name":"Korea University of Science and Technology","ror":"https://ror.org/000qzf213","country_code":"KR","type":"education","lineage":["https://openalex.org/I88761825"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yong-Hyuk Moon","raw_affiliation_strings":["Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute(ETRI) University of Science and Technology(UST),Daejeon,Korea","Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute(ETRI) University of Science and Technology(UST), Daejeon, Korea"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute(ETRI) University of Science and Technology(UST),Daejeon,Korea","institution_ids":["https://openalex.org/I142401562"]},{"raw_affiliation_string":"Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute(ETRI) University of Science and Technology(UST), Daejeon, Korea","institution_ids":["https://openalex.org/I142401562","https://openalex.org/I88761825"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100695869"],"corresponding_institution_ids":["https://openalex.org/I142401562"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11692571,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"abs 1706 4599","issue":null,"first_page":"495","last_page":"497"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8659681081771851},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7253432273864746},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6477575302124023},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5455678105354309},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5384523868560791},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4999852180480957},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4966731667518616},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.44383466243743896},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4130544364452362},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.41246476769447327},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3420504927635193},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19534572958946228}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8659681081771851},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7253432273864746},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6477575302124023},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5455678105354309},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5384523868560791},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4999852180480957},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4966731667518616},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.44383466243743896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4130544364452362},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.41246476769447327},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3420504927635193},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19534572958946228},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictc55196.2022.9953031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc55196.2022.9953031","pdf_url":null,"source":{"id":"https://openalex.org/S4363607740","display_name":"2022 13th International Conference on Information and Communication Technology Convergence (ICTC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 13th International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2604231779","https://openalex.org/W2626967530","https://openalex.org/W2955425717","https://openalex.org/W2962677625","https://openalex.org/W2963163009","https://openalex.org/W3093805012","https://openalex.org/W4200012447","https://openalex.org/W6739651123"],"related_works":["https://openalex.org/W4386245174","https://openalex.org/W4313339048","https://openalex.org/W4200132709","https://openalex.org/W3013760193","https://openalex.org/W3162668736","https://openalex.org/W4366999913","https://openalex.org/W4281678247","https://openalex.org/W4386004629","https://openalex.org/W3176734149","https://openalex.org/W4381489698"],"abstract_inverted_index":{"Modern":[0],"edge":[1],"devices":[2],"have":[3],"become":[4],"powerful":[5],"enough":[6],"to":[7,47,92,145],"run":[8],"deep":[9],"learning":[10],"tasks,":[11],"but":[12],"there":[13],"are":[14],"still":[15],"many":[16],"challenges,":[17,33],"such":[18,22,35],"as":[19,23,36],"limited":[20],"resources":[21],"computing":[24],"power,":[25],"memory":[26,140],"space,":[27],"and":[28,41,88,111,130,133,142],"energy.":[29],"To":[30],"address":[31],"these":[32],"methods":[34],"channel":[37],"pruning,":[38],"network":[39,64,104,115],"quantization":[40],"early":[42,71],"exiting":[43,72],"has":[44],"been":[45],"introduced":[46],"reduce":[48],"the":[49,85,94,98,103,108,114,117],"computational":[50,95],"load":[51,110],"for":[52,119],"achieve":[53],"this":[54,57],"tasks.":[55],"In":[56],"paper,":[58],"we":[59],"propose":[60],"LazyNet,":[61],"an":[62],"alternative":[63],"of":[65,70,107],"applying":[66],"skip":[67],"modules":[68],"instead":[69],"on":[73,136],"a":[74,80],"pre-trained":[75],"neural":[76],"network.":[77],"We":[78,122],"use":[79],"small":[81],"module":[82],"that":[83],"preserves":[84],"spatial":[86],"information":[87],"also":[89],"provides":[90],"metrics":[91],"decide":[93],"flow.":[96],"If":[97],"data":[99],"sample":[100,118],"is":[101],"easy,":[102],"skips":[105],"most":[106],"computation":[109],"if":[112],"not,":[113],"computes":[116],"accurate":[120],"classification.":[121],"test":[123],"our":[124,147],"model":[125,137],"with":[126],"various":[127],"backbone":[128],"networks":[129],"cifar-10":[131],"dataset":[132],"show":[134],"reduction":[135],"inference":[138],"time,":[139],"consumption":[141],"increased":[143],"accuracy":[144],"prove":[146],"results.":[148]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
