{"id":"https://openalex.org/W2910343334","doi":"https://doi.org/10.1145/3287624.3287643","title":"CAPTOR","display_name":"CAPTOR","publication_year":2019,"publication_date":"2019-01-18","ids":{"openalex":"https://openalex.org/W2910343334","doi":"https://doi.org/10.1145/3287624.3287643","mag":"2910343334"},"language":"en","primary_location":{"id":"doi:10.1145/3287624.3287643","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3287624.3287643","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3287624.3287643","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th Asia and South Pacific Design Automation Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3287624.3287643","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018832267","display_name":"Zhuwei Qin","orcid":"https://orcid.org/0000-0002-5465-7740"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhuwei Qin","raw_affiliation_strings":["George Mason University"],"affiliations":[{"raw_affiliation_string":"George Mason University","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103085687","display_name":"Fuxun Yu","orcid":"https://orcid.org/0000-0002-4880-6658"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fuxun Yu","raw_affiliation_strings":["George Mason University"],"affiliations":[{"raw_affiliation_string":"George Mason University","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767202","display_name":"Chenchen Liu","orcid":"https://orcid.org/0000-0001-7749-0640"},"institutions":[{"id":"https://openalex.org/I16944753","display_name":"Clarkson University","ror":"https://ror.org/03rwgpn18","country_code":"US","type":"education","lineage":["https://openalex.org/I16944753"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenchen Liu","raw_affiliation_strings":["Clarkson University"],"affiliations":[{"raw_affiliation_string":"Clarkson University","institution_ids":["https://openalex.org/I16944753"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100441957","display_name":"Xiang Chen","orcid":"https://orcid.org/0000-0003-2790-976X"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiang Chen","raw_affiliation_strings":["George Mason University"],"affiliations":[{"raw_affiliation_string":"George Mason University","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5018832267"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":0.5061,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.67631978,"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":"444","last_page":"449"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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":0.9994000196456909,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.987500011920929,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7714115381240845},{"id":"https://openalex.org/keywords/control-reconfiguration","display_name":"Control reconfiguration","score":0.6379443407058716},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6199248433113098},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5406531691551208},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5074705481529236},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4859718084335327},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.45783331990242004},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.4386017918586731},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4340536296367645},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4286423325538635},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.41369760036468506},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4014877378940582},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22316670417785645},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.1592389941215515},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13637930154800415},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11262589693069458},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09072738885879517}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7714115381240845},{"id":"https://openalex.org/C119701452","wikidata":"https://www.wikidata.org/wiki/Q5165881","display_name":"Control reconfiguration","level":2,"score":0.6379443407058716},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6199248433113098},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5406531691551208},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5074705481529236},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4859718084335327},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.45783331990242004},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.4386017918586731},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4340536296367645},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4286423325538635},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.41369760036468506},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4014877378940582},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22316670417785645},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.1592389941215515},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13637930154800415},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11262589693069458},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09072738885879517},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3287624.3287643","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3287624.3287643","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3287624.3287643","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th Asia and South Pacific Design Automation Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3287624.3287643","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3287624.3287643","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3287624.3287643","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th Asia and South Pacific Design Automation Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G4287288835","display_name":null,"funder_award_id":"1717775","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2910343334.pdf","grobid_xml":"https://content.openalex.org/works/W2910343334.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1845051632","https://openalex.org/W1849277567","https://openalex.org/W1996901117","https://openalex.org/W2001996312","https://openalex.org/W2279098554","https://openalex.org/W2495112539","https://openalex.org/W2525098248","https://openalex.org/W2612445135","https://openalex.org/W2618530766","https://openalex.org/W2889185260","https://openalex.org/W2950837708","https://openalex.org/W2964299589","https://openalex.org/W3118608800"],"related_works":["https://openalex.org/W1981002473","https://openalex.org/W2357657342","https://openalex.org/W2153432761","https://openalex.org/W2152623100","https://openalex.org/W2142042635","https://openalex.org/W4214878056","https://openalex.org/W1580144672","https://openalex.org/W1988127757","https://openalex.org/W4293061881","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Nowadays,":[0],"the":[1,61,88,109],"evolution":[2],"of":[3,92,152],"deep":[4],"learning":[5],"and":[6,18,57,67,99,106,125,145,165],"cloud":[7],"service":[8],"significantly":[9],"promotes":[10],"neural":[11,29],"network":[12,122],"based":[13],"mobile":[14,54,129],"applications.":[15],"Although":[16],"intelligent":[17],"prolific,":[19],"those":[20],"applications":[21],"still":[22],"lack":[23],"certain":[24],"flexibility:":[25],"For":[26,154],"classification":[27,37],"tasks,":[28],"networks":[30],"are":[31,48],"generally":[32],"trained":[33],"online":[34],"with":[35,112,149,169],"vast":[36],"targets":[38],"to":[39,52,143,163],"cover":[40],"various":[41],"utilization":[42],"contexts.":[43],"However,":[44],"only":[45],"partial":[46],"classes":[47,63],"practically":[49],"tested":[50],"due":[51],"individual":[53],"user":[55],"preference":[56,91],"application":[58],"specificity.":[59],"Thus":[60],"unneeded":[62,113],"cause":[64],"considerable":[65],"computation":[66,137,159],"communication":[68],"cost.":[69],"In":[70],"this":[71],"work,":[72],"we":[73],"propose":[74],"CAPTOR":[75,102,116,134,156],"-":[76],"a":[77],"class-level":[78,118],"reconfiguration":[79,120],"framework":[80],"for":[81,121,139],"Convolutional":[82],"Neural":[83],"Networks":[84],"(CNNs).":[85],"By":[86],"identifying":[87],"class":[89],"activation":[90],"convolutional":[93],"filters":[94,110],"through":[95],"feature":[96],"interest":[97],"visualization":[98],"gradient":[100],"analysis,":[101],"can":[103,135],"effectively":[104],"cluster":[105],"adaptively":[107],"prune":[108],"associated":[111],"classes.":[114],"Therefore,":[115],"enables":[117],"CNN":[119],"model":[123],"compression":[124],"local":[126],"deployment":[127],"on":[128],"devices.":[130],"Experiment":[131],"shows":[132],"that,":[133],"reduce":[136],"load":[138,160],"VGG-16":[140],"by":[141,161],"up":[142,162],"40.5%":[144],"37.9%":[146],"energy":[147,167],"consumption":[148,168],"ignored":[150],"loss":[151,173],"accuracy.":[153,175],"AlexNet,":[155],"also":[157],"reduces":[158],"42.8%":[164],"37.6%":[166],"less":[170],"than":[171],"3%":[172],"in":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-01-25T00:00:00"}
