{"id":"https://openalex.org/W3030364186","doi":"https://doi.org/10.1109/icpr48806.2021.9412949","title":"Improving Batch Normalization with Skewness Reduction for Deep Neural Networks","display_name":"Improving Batch Normalization with Skewness Reduction for Deep Neural Networks","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3030364186","doi":"https://doi.org/10.1109/icpr48806.2021.9412949","mag":"3030364186"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5025773749","display_name":"Pak Lun Kevin Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pak Lun Kevin Ding","raw_affiliation_strings":["School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ"],"affiliations":[{"raw_affiliation_string":"School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113508549","display_name":"Sarah Martin","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sarah Martin","raw_affiliation_strings":["School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ"],"affiliations":[{"raw_affiliation_string":"School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032615847","display_name":"Baoxin Li","orcid":"https://orcid.org/0000-0002-9294-4572"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baoxin Li","raw_affiliation_strings":["School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ"],"affiliations":[{"raw_affiliation_string":"School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025773749"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":0.1921,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.44826797,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"abs 1607 8022","issue":null,"first_page":"7165","last_page":"7172"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9990000128746033,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9987000226974487,"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/normalization","display_name":"Normalization (sociology)","score":0.939811110496521},{"id":"https://openalex.org/keywords/skewness","display_name":"Skewness","score":0.8681150078773499},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6442912817001343},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5930742621421814},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5180764198303223},{"id":"https://openalex.org/keywords/spatial-normalization","display_name":"Spatial normalization","score":0.513282060623169},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5126311182975769},{"id":"https://openalex.org/keywords/variance-reduction","display_name":"Variance reduction","score":0.5053451657295227},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4454430937767029},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4408695697784424},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41311341524124146},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4125479459762573},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2792162001132965},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20896872878074646},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.07118791341781616}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.939811110496521},{"id":"https://openalex.org/C122342681","wikidata":"https://www.wikidata.org/wiki/Q330828","display_name":"Skewness","level":2,"score":0.8681150078773499},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6442912817001343},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5930742621421814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5180764198303223},{"id":"https://openalex.org/C116580362","wikidata":"https://www.wikidata.org/wiki/Q3878457","display_name":"Spatial normalization","level":3,"score":0.513282060623169},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5126311182975769},{"id":"https://openalex.org/C62644790","wikidata":"https://www.wikidata.org/wiki/Q3454689","display_name":"Variance reduction","level":3,"score":0.5053451657295227},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4454430937767029},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4408695697784424},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41311341524124146},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4125479459762573},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2792162001132965},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20896872878074646},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.07118791341781616},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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":48,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1686810756","https://openalex.org/W1815076433","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1981530182","https://openalex.org/W2034276439","https://openalex.org/W2117539524","https://openalex.org/W2127230474","https://openalex.org/W2134583763","https://openalex.org/W2161388792","https://openalex.org/W2163605009","https://openalex.org/W2176412452","https://openalex.org/W2284050935","https://openalex.org/W2302255633","https://openalex.org/W2342662179","https://openalex.org/W2502312327","https://openalex.org/W2546302380","https://openalex.org/W2594833348","https://openalex.org/W2780544323","https://openalex.org/W2786811008","https://openalex.org/W2899771611","https://openalex.org/W2914484425","https://openalex.org/W2949117887","https://openalex.org/W2951603627","https://openalex.org/W2962972936","https://openalex.org/W2963285578","https://openalex.org/W2963399222","https://openalex.org/W2963446712","https://openalex.org/W2963454111","https://openalex.org/W2963685250","https://openalex.org/W3118608800","https://openalex.org/W4255949318","https://openalex.org/W4297779039","https://openalex.org/W6631943919","https://openalex.org/W6638545294","https://openalex.org/W6639824700","https://openalex.org/W6658987400","https://openalex.org/W6679022428","https://openalex.org/W6680172675","https://openalex.org/W6683595889","https://openalex.org/W6684191040","https://openalex.org/W6695676441","https://openalex.org/W6698183232","https://openalex.org/W6724804524","https://openalex.org/W6729344799","https://openalex.org/W6739879593","https://openalex.org/W6755310813"],"related_works":["https://openalex.org/W2189529952","https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W2140186469","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W2775233965","https://openalex.org/W4318559728","https://openalex.org/W4360995913","https://openalex.org/W4313400923"],"abstract_inverted_index":{"Batch":[0,122],"Normalization":[1,123],"(BN)":[2],"is":[3,19],"a":[4,32,38,44,118,154],"well-known":[5],"technique":[6],"used":[7],"in":[8,92],"training":[9],"deep":[10],"neural":[11],"networks.":[12],"The":[13,171],"main":[14],"idea":[15],"behind":[16],"batch":[17],"normalization":[18,120,131,187],"to":[20,30,35,41,54,111,159,167],"normalize":[21],"the":[22,25,47,51,59,62,75,78,84,87,90,93,109,113,138,144,147,161,165,178,181,192,201],"features":[23,88,110],"of":[24,50,61,77,86,89,146,153,164,173,180],"layers":[26,166],"(i.e.,":[27],"transforming":[28],"them":[29],"have":[31,112],"mean":[33,102,139],"equal":[34,40],"zero":[36],"and":[37,57,67,103,140,194],"variance":[39,104],"one).":[42],"Such":[43],"procedure":[45],"encourages":[46],"optimization":[48],"landscape":[49],"loss":[52],"function":[53],"be":[55,81,168],"smoother,":[56],"improves":[58],"learning":[60],"networks":[63],"for":[64],"both":[65],"speed":[66],"performance.":[68],"In":[69],"this":[70,151],"paper,":[71],"we":[72,116,156],"demonstrate":[73],"that":[74,200,208],"performance":[76],"network":[79],"can":[80,204],"improved,":[82],"if":[83],"distributions":[85,163],"output":[91,162],"same":[94,114],"layer":[95],"are":[96,157,189,209],"similar.":[97,170],"As":[98],"normalizing":[99],"based":[100],"on":[101,191],"does":[105],"not":[106,135,210],"necessarily":[107],"make":[108,160],"distribution,":[115,155],"propose":[117],"new":[119],"scheme:":[121],"with":[124,129,185,212],"Skewness":[125],"Reduction":[126],"(BNSR).":[127],"Comparing":[128],"other":[130,186,206],"approaches,":[132],"BNSR":[133,174],"transforms":[134],"just":[136],"only":[137],"variance,":[141],"but":[142],"also":[143],"skewness":[145],"data.":[148],"By":[149],"tackling":[150],"property":[152],"able":[158],"further":[169,176],"nonlinearity":[172],"may":[175],"improve":[177],"expressiveness":[179],"underlying":[182],"network.":[183],"Comparisons":[184],"schemes":[188],"tested":[190],"CIFAR-100":[193],"ImageNet":[195],"datasets.":[196],"Experimental":[197],"results":[198],"show":[199],"proposed":[202],"approach":[203],"outperform":[205],"state-of-the-arts":[207],"equipped":[211],"BNSR.":[213]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}