{"id":"https://openalex.org/W4388280117","doi":"https://doi.org/10.1109/icbase59196.2023.10303152","title":"Compression for the Pointwise Convolution - Feature Fusion","display_name":"Compression for the Pointwise Convolution - Feature Fusion","publication_year":2023,"publication_date":"2023-08-25","ids":{"openalex":"https://openalex.org/W4388280117","doi":"https://doi.org/10.1109/icbase59196.2023.10303152"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbase59196.2023.10303152","pdf_url":null,"source":null,"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/A5100442711","display_name":"Zhiwei Chen","orcid":"https://orcid.org/0000-0002-5474-3630"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Chen","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440826","display_name":"Can Zhang","orcid":"https://orcid.org/0000-0001-9530-5218"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Can Zhang","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078266278","display_name":"Deyuan Chen","orcid":"https://orcid.org/0000-0003-4280-574X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deyuan Chen","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086763568","display_name":"Shaoshuai Gao","orcid":"https://orcid.org/0000-0001-7958-2717"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoshuai Gao","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"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":false,"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":65},"biblio":{"volume":null,"issue":null,"first_page":"6","last_page":"13"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9996,"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":0.9996,"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/T10812","display_name":"Human Pose and Action Recognition","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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9974,"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/pointwise","display_name":"Pointwise","score":0.95757365},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.80711186},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.67927945},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.6383788},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48523545},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.45026472}],"concepts":[{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.95757365},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.80711186},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.67927945},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.6383788},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5815718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.52622914},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49869275},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48523545},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.45026472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43716472},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4036975},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3947183},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1661284},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.11382216},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.07123026},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.05767128},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","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":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbase59196.2023.10303152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"grants":[{"funder":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities","award_id":null}],"datasets":[],"versions":[],"referenced_works_count":18,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1996901117","https://openalex.org/W2097117768","https://openalex.org/W2112796928","https://openalex.org/W2133665775","https://openalex.org/W2194775991","https://openalex.org/W2525098248","https://openalex.org/W2549139847","https://openalex.org/W2605135468","https://openalex.org/W2618530766","https://openalex.org/W2884585870","https://openalex.org/W2962988160","https://openalex.org/W2963172626","https://openalex.org/W2964233199","https://openalex.org/W3034752215","https://openalex.org/W3035414587","https://openalex.org/W3118608800","https://openalex.org/W4285505364"],"related_works":["https://openalex.org/W4386858688","https://openalex.org/W4380302312","https://openalex.org/W4361003569","https://openalex.org/W4288417960","https://openalex.org/W3034421924","https://openalex.org/W2995343971","https://openalex.org/W2992221004","https://openalex.org/W2982536526","https://openalex.org/W2981421796","https://openalex.org/W2921438861"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"have":[4],"proposed":[5],"a":[6],"method":[7,99],"to":[8],"measure":[9],"the":[10,22,31,38,45,48,53,56,62,67,74,78,83,90,97,109,123,127,145,148,152],"weight":[11,23,149],"efficiency":[12,24,146],"of":[13,25,37,47,55,69,77,120,130,135,139,147,151],"pointwise":[14,26,57,79,153],"convolution":[15,27,58,80,154],"(weight":[16],"sharing":[17],"index),":[18],"which":[19],"finds":[20],"that":[21,96],"decreases":[28],"rapidly":[29],"as":[30],"network":[32],"becomes":[33],"deeper.":[34],"The":[35,87],"redundancy":[36],"feature":[39,49,64,85,104],"maps":[40,65,105],"is":[41],"mainly":[42],"reflected":[43],"in":[44,122],"similarity":[46,71],"maps.":[50,86],"We":[51],"achieve":[52],"compression":[54,98],"layers":[59],"by":[60,81,132],"quantifying":[61],"similar":[63,84,103],"with":[66,117],"help":[68],"structural":[70],"(SSIM),":[72],"reducing":[73],"input":[75],"channels":[76],"fusing":[82,102],"results":[88],"on":[89,101],"datasets":[91],"CIFAR-10":[92],"and":[93,112,137,143],"CIFAR-100":[94],"demonstrate":[95],"based":[100],"can":[106],"significantly":[107],"compress":[108],"MobileNet-V1(48.74%":[110],"FLOPs":[111,136],"13.64%":[113],"parameters":[114,140],"are":[115,141],"reduced)":[116],"an":[118],"increase":[119],"0.54%":[121],"top-1":[124,128],"accuracy,":[125],"improving":[126],"accuracy":[129],"ResNet-50":[131],"0.09%":[133],"(9.2%":[134],"6.03%":[138],"reduced),":[142],"improves":[144],"utilization":[150],"layer.":[155]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4388280117","counts_by_year":[],"updated_date":"2025-04-13T01:48:09.467700","created_date":"2023-11-04"}