Sept. 2, 2022, 1:15 a.m. | Zhennan Wang, Kehan Li, Runyi Yu, Yian Zhao, Pengchong Qiao, Guoli Song, Fan Xu, Jie Chen

cs.CV updates on arXiv.org arxiv.org

In this paper, we show that the difference in $l_2$ norms of sample features
can hinder batch normalization from obtaining more distinguished inter-class
features and more compact intra-class features. To address this issue, we
propose an intuitive but effective method to equalize the $l_2$ norms of sample
features. Concretely, we $l_2$-normalize each sample feature before batch
normalization, and therefore the features are of the same magnitude. Since the
proposed method combines the $l_2$ normalization and batch normalization, we
name our …

arxiv features normalization

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Stagista Technical Data Engineer

@ Hager Group | BRESCIA, IT

Data Analytics - SAS, SQL - Associate

@ JPMorgan Chase & Co. | Mumbai, Maharashtra, India