乐胖代购免代理版

{"id":"https://openalex.org/W2792228668","doi":"https://doi.org/10.1109/icip.2017.8297115","title":"A novel method to regenerate an optimal CNN by exploiting redundancy patterns in the network","display_name":"A novel method to regenerate an optimal CNN by exploiting redundancy patterns in the network","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2792228668","doi":"https://doi.org/10.1109/icip.2017.8297115","mag":"2792228668"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8297115","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5038794404","display_name":"Sirish Kumar Pasupuleti","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sirish Kumar Pasupuleti","raw_affiliation_strings":["Samsung R&D Institute India-Bangalore Pvt. Ltd., Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute India-Bangalore Pvt. Ltd., Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031971317","display_name":"Narasinga Rao Miniskar","orcid":"https://orcid.org/0000-0001-8259-8891"},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Narasinga Rao Miniskar","raw_affiliation_strings":["Samsung R&D Institute India-Bangalore Pvt. Ltd., Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute India-Bangalore Pvt. Ltd., Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070988453","display_name":"Vasanthakumar Rajagopal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vasanthakumar Rajagopal","raw_affiliation_strings":["Samsung R&D Institute India-Bangalore Pvt. Ltd., Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute India-Bangalore Pvt. Ltd., Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085051959","display_name":"Raj Narayana Gadde","orcid":null},"institutions":[{"id":"https://openalex.org/I4210139030","display_name":"Samsung (India)","ror":"https://ror.org/04cpx2569","country_code":"IN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210139030"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Raj Narayana Gadde","raw_affiliation_strings":["Samsung R&D Institute India-Bangalore Pvt. Ltd., Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Samsung R&D Institute India-Bangalore Pvt. Ltd., Bangalore, India","institution_ids":["https://openalex.org/I4210139030"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":63},"biblio":{"volume":null,"issue":null,"first_page":"4407","last_page":"4411"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9999,"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":0.9999,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.999,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9979,"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/pruning","display_name":"Pruning","score":0.4698621},{"id":"https://openalex.org/keywords/high-memory","display_name":"High memory","score":0.4453969}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.84111595},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6511796},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.550496},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4698621},{"id":"https://openalex.org/C2781357197","wikidata":"https://www.wikidata.org/wiki/Q5757597","display_name":"High memory","level":2,"score":0.4453969},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3460797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2662086},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8297115","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.59,"display_name":"Affordable and clean energy"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":14,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2152332944","https://openalex.org/W2155893237","https://openalex.org/W2172654076","https://openalex.org/W2194775991","https://openalex.org/W2233116163","https://openalex.org/W2395118064","https://openalex.org/W2509388930","https://openalex.org/W2962835968","https://openalex.org/W2962965870","https://openalex.org/W2963981420","https://openalex.org/W2964299589"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4206442282","https://openalex.org/W2594301978","https://openalex.org/W2395294869","https://openalex.org/W2384505857","https://openalex.org/W2379704676","https://openalex.org/W2378744544","https://openalex.org/W2373300491","https://openalex.org/W2355171581","https://openalex.org/W1998810860"],"abstract_inverted_index":{"Deploying":[0],"Convolution":[1],"Neural":[2],"Networks":[3],"(CNN)":[4],"based":[5,71],"computer":[6],"vision":[7],"applications":[8],"on":[9,26,72,129],"low-power":[10],"embedded":[11],"devices":[12],"is":[13,24,118],"challenging":[14],"due":[15],"to":[16,35,55,87,110],"massive":[17],"computation":[18],"and":[19,31,59,78,80,92,106,147,155],"memory":[20,93,148,157],"bandwidth":[21],"requirements.":[22],"Research":[23],"on-going":[25],"faster":[27],"algorithms,":[28],"network":[29,54,160],"pruning,":[30],"model":[32,107],"compression":[33,108],"techniques":[34,109],"produce":[36],"light-weight":[37],"networks.":[38],"In":[39],"this":[40],"paper,":[41],"we":[42],"propose":[43],"a":[44,49,64],"novel":[45],"method":[46,101,117],"which":[47],"exploits":[48],"redundancy":[50],"pattern":[51,70],"in":[52,145],"the":[53,69,73,85,89,103,121],"regenerate":[56],"an":[57,133,141],"efficient":[58],"functionally":[60],"identical":[61,97],"CNN":[62],"for":[63,125],"given":[65],"network.":[66],"We":[67],"identify":[68],"layer":[74,150],"parameters":[75],"(kernel":[76],"size":[77],"stride)":[79],"data":[81],"flow":[82],"analysis":[83],"among":[84],"layers":[86],"avoid":[88],"redundant":[90],"processing":[91],"requirements":[94],"while":[95],"maintaining":[96],"accuracy.":[98],"Our":[99],"proposed":[100,116],"augments":[102],"state-of-the-art":[104],"pruning":[105],"achieve":[111],"further":[112],"performance":[113,146,153],"boost-up.":[114],"The":[115,138],"experimented":[119],"with":[120,132],"Caffe":[122],"[1]":[123],"framework":[124],"ResNet-50":[126],"[2]":[127],"inference":[128],"Samsung":[130],"smartphone":[131],"octa-core":[134],"ARM":[135],"Cortex-A53":[136],"processor.":[137],"results":[139],"show":[140],"improvement":[142,154],"of":[143],"4x":[144],"at":[149,159],"level,":[151],"~22%":[152],"6%":[156],"reduction":[158],"level.":[161]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2792228668","counts_by_year":[],"updated_date":"2025-01-19T09:48:42.538172","created_date":"2018-03-29"}