Large Neural Networks Learning from Scratch with Very Few Data and without Explicit Regularization-Reference-Cited by-同舟云学术

Large Neural Networks Learning from Scratch with Very Few Data and without Explicit Regularization

Published:2023-02-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 15th International Conference on Machine Learning and Computing
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Author:

Linse Christoph¹^ORCID,Martinetz Thomas¹^ORCID

Affiliation:

1. Institute for Neuro- and Bioinformatics, University of Lübeck, Germany

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3587716.3587780

Reference17 articles.

1. Hammam Alshazly , Christoph Linse , Erhardt Barth , and Thomas Martinetz . 2019. Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition. sensors 19, 19 ( 2019 ), 4139. https://www.mdpi.com/1424-8220/19/19/4139 Hammam Alshazly, Christoph Linse, Erhardt Barth, and Thomas Martinetz. 2019. Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition. sensors 19, 19 (2019), 4139. https://www.mdpi.com/1424-8220/19/19/4139

2. Anne L Alter and Karen M Wang. 2017. An Exploration of Computer Vision Techniques for Bird Species Classification. Anne L Alter and Karen M Wang. 2017. An Exploration of Computer Vision Techniques for Bird Species Classification.

3. Reconciling modern machine-learning practice and the classical bias–variance trade-off

4. ImageNet: A large-scale hierarchical image database

5. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

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