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1905.13613
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Regression Networks for Meta-Learning Few-Shot Classification

v1v2 (latest)

Regression Networks for Meta-Learning Few-Shot Classification

31 May 2019

Matthias Grossglauser

ArXiv (abs)PDF HTML

Papers citing "Regression Networks for Meta-Learning Few-Shot Classification"

5 / 5 papers shown

Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-rays

Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-raysIEEE International Symposium on Biomedical Imaging (ISBI), 2021

Behzad Bozorgtabar

Jean-Philippe Thiran

238

17

0

19 Feb 2021

Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task
Generalization in Few-shot Learning

Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning

Lauren A. Phillips

Court D. Corley

Nathan Oken Hodas

161

2

0

23 Sep 2020

Explanation-Guided Training for Cross-Domain Few-Shot Classification

Explanation-Guided Training for Cross-Domain Few-Shot ClassificationInternational Conference on Pattern Recognition (ICPR), 2020

Sebastian Lapuschkin

Ngai-Man Cheung

Alexander Binder

352

115

0

17 Jul 2020

Self-Supervised Prototypical Transfer Learning for Few-Shot
Classification

Self-Supervised Prototypical Transfer Learning for Few-Shot Classification

Matthias Grossglauser

248

57

0

19 Jun 2020

TAFSSL: Task-Adaptive Feature Sub-Space Learning for few-shot
classification

TAFSSL: Task-Adaptive Feature Sub-Space Learning for few-shot classificationEuropean Conference on Computer Vision (ECCV), 2020

M. Lichtenstein

Leonid Karlinsky

237

81

0

14 Mar 2020

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