Population Gradients improve performance across data-sets and architectures in object classification

Yurika Sakai, Andrey Kormilitzin, Qiang Liu, Alejo Nevado-Holgado

Research output: Contribution to journal › Article (Academic Journal)

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@article{e7d2f5a959f049b1a9348f7eddbaa5da,

title = "Population Gradients improve performance across data-sets and architectures in object classification",

author = "Yurika Sakai and Andrey Kormilitzin and Qiang Liu and Alejo Nevado-Holgado",

year = "2020",

month = oct,

day = "23",

doi = "https://doi.org/10.48550/arXiv.2010.12260",

language = "English",

journal = "arXiv preprint",

}

TY - JOUR

T1 - Population Gradients improve performance across data-sets and architectures in object classification

AU - Sakai, Yurika

AU - Kormilitzin, Andrey

AU - Liu, Qiang

AU - Nevado-Holgado, Alejo

PY - 2020/10/23

Y1 - 2020/10/23

U2 - https://doi.org/10.48550/arXiv.2010.12260

DO - https://doi.org/10.48550/arXiv.2010.12260

M3 - Article (Academic Journal)

JO - arXiv preprint

JF - arXiv preprint

ER -