{"id":"https://openalex.org/W4318603360","doi":"https://doi.org/10.1109/ssci51031.2022.10022267","title":"Generalwise Separable Convolution for Mobile Vision Applications","display_name":"Generalwise Separable Convolution for Mobile Vision Applications","publication_year":2022,"publication_date":"2022-12-04","ids":{"openalex":"https://openalex.org/W4318603360","doi":"https://doi.org/10.1109/ssci51031.2022.10022267"},"language":"en","primary_location":{"id":"doi:10.1109/ssci51031.2022.10022267","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ssci51031.2022.10022267","pdf_url":null,"source":{"id":"https://openalex.org/S4363605327","display_name":"2022 IEEE Symposium Series on Computational Intelligence (SSCI)","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 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5010022745","display_name":"Shicheng Zu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shicheng Zu","raw_affiliation_strings":["Ericsson Pandas Communications Co. Ltd,Nanjing,China,211106"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson Pandas Communications Co. Ltd,Nanjing,China,211106","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048434881","display_name":"Yucheng Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210152119","display_name":"Jiangsu Province Hospital","ror":"https://ror.org/04py1g812","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210152119"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yucheng Jin","raw_affiliation_strings":["Jiangsu Province Hospital on Integration of Chinese and Western Medicine,Nanjing,China,210028"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangsu Province Hospital on Integration of Chinese and Western Medicine,Nanjing,China,210028","institution_ids":["https://openalex.org/I4210152119"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100447990","display_name":"Yang Li","orcid":"https://orcid.org/0000-0003-1682-0284"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["Artificial Intelligence Lab, CRGROUP Inc.,Nanjing,China,210019"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Lab, CRGROUP Inc.,Nanjing,China,210019","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0925,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43404657,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1074","last_page":"1081"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991000294685364,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7551984786987305},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.7318781018257141},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6229864954948425},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.5472114682197571},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5270426869392395},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5013546943664551},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4818657338619232},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4606691598892212},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.44507065415382385},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.43474555015563965},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4255122244358063},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4132271707057953},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36134451627731323},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34309127926826477},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3002704977989197},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20407846570014954},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.07417252659797668}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7551984786987305},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.7318781018257141},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6229864954948425},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.5472114682197571},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5270426869392395},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5013546943664551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4818657338619232},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4606691598892212},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.44507065415382385},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.43474555015563965},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4255122244358063},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4132271707057953},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36134451627731323},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34309127926826477},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3002704977989197},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20407846570014954},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.07417252659797668},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci51031.2022.10022267","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ssci51031.2022.10022267","pdf_url":null,"source":{"id":"https://openalex.org/S4363605327","display_name":"2022 IEEE Symposium Series on Computational Intelligence (SSCI)","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 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1650736245","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W1902041153","https://openalex.org/W1935978687","https://openalex.org/W1983364832","https://openalex.org/W1996901117","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2279098554","https://openalex.org/W2531409750","https://openalex.org/W2570343428","https://openalex.org/W2883780447","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963225922","https://openalex.org/W2963419583","https://openalex.org/W2963446712","https://openalex.org/W2963623257","https://openalex.org/W2963821229","https://openalex.org/W2963844898","https://openalex.org/W2963918968","https://openalex.org/W2963976704","https://openalex.org/W2963993763","https://openalex.org/W2964081807","https://openalex.org/W2965658867","https://openalex.org/W2982083293","https://openalex.org/W2989373050","https://openalex.org/W3094502228","https://openalex.org/W3106250896","https://openalex.org/W3118608800","https://openalex.org/W3215449256","https://openalex.org/W4281816350","https://openalex.org/W4293450887","https://openalex.org/W4297775537","https://openalex.org/W6637078681","https://openalex.org/W6637373629","https://openalex.org/W6638444622","https://openalex.org/W6685891324","https://openalex.org/W6686024063","https://openalex.org/W6695314431","https://openalex.org/W6753441378","https://openalex.org/W6753767121","https://openalex.org/W6784333009"],"related_works":["https://openalex.org/W2582836483","https://openalex.org/W4299366318","https://openalex.org/W2530952058","https://openalex.org/W4297580547","https://openalex.org/W2760085659","https://openalex.org/W2295021132","https://openalex.org/W3106036237","https://openalex.org/W2980776160","https://openalex.org/W2949528695","https://openalex.org/W2891179104"],"abstract_inverted_index":{"It":[0],"is":[1,87,132,176],"acknowledged":[2],"that":[3,127,151,181,188],"the":[4,10,24,35,39,48,52,58,63,68,91,97,128,135,145],"depthwise":[5,19,59,136],"separable":[6,54,60,93,99,130,137],"convolution":[7,20,55,61,100,131,138],"effectively":[8],"reduces":[9],"computational":[11],"complexity":[12],"of":[13,76,104,182,189],"a":[14,102,114],"standard":[15],"convolution.":[16,94],"However,":[17],"its":[18],"only":[21],"performs":[22],"on":[23,201],"spatial":[25,64,146],"domain":[26,65],"while":[27],"neglecting":[28],"to":[29,56,66,89,134],"consider":[30],"other":[31,154],"domains":[32,143],"such":[33],"as":[34,113],"one":[36],"formed":[37],"by":[38,50,139],"channel":[40,80,82],"and":[41,70,84,184,199],"width/height":[42],"dimensions.":[43],"This":[44],"paper":[45],"specifically":[46],"bridges":[47],"gaps":[49],"proposing":[51],"generalwise":[53,92,98,129],"generalize":[57],"beyond":[62],"recruit":[67],"widthwise":[69],"heightwise":[71],"convolutions.":[72],"A":[73],"sequential":[74],"combination":[75],"pointwise":[77],"group":[78],"convolution,":[79],"shuffling,":[81],"splitting,":[83],"dimension":[85],"transposing":[86],"required":[88],"implement":[90],"By":[95],"embedding":[96],"into":[101],"stack":[103],"inverted":[105],"residuals":[106],"with":[107,172],"linear":[108],"bottlenecks,":[109],"we":[110],"propose":[111],"GSCNet":[112,152,167,191],"lightweight":[115],"neural":[116],"backbone":[117],"for":[118],"various":[119],"embedded":[120],"vision":[121,160],"tasks.":[122,161],"Our":[123],"empirical":[124],"evidence":[125],"indicates":[126],"superior":[133],"feature":[140],"extraction":[141],"from":[142],"complementing":[144],"domain.":[147],"Experimental":[148],"results":[149],"show":[150],"outperforms":[153],"state-of-the-art":[155],"mobile":[156],"CNNs":[157],"over":[158],"multiply":[159],"On":[162],"ImageNet":[163],"object":[164,203],"classification":[165],"benchmark,":[166],"achieves":[168],"75.5%":[169],"top-1":[170],"accuracy":[171],"216.98M":[173],"multiply-adds,":[174],"which":[175],"28.1":[177],"%":[178],"fewer":[179,186],"than":[180,187,197],"MobileNetv2":[183],"29.3%":[185],"HBONet.":[190],"also":[192],"yields":[193],"better":[194],"mAP":[195],"quality":[196],"MobileNetv1/v2":[198],"MnasNet":[200],"COCO":[202],"detection":[204],"benchmark.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
