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Complementing Representation Deficiency in Few-shot Image
  Classification: A Meta-Learning Approach

Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning Approach

21 July 2020
X. Zhong
Cheng Gu
Wenxin Huang
Lin Li
Shuqin Chen
Chia-Wen Lin
    SSL
ArXivPDFHTML

Papers citing "Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning Approach"

5 / 5 papers shown
Title
Out-of-distribution Few-shot Learning For Edge Devices without Model
  Fine-tuning
Out-of-distribution Few-shot Learning For Edge Devices without Model Fine-tuning
Xinyun Zhang
Lanqing Hong
OODD
25
0
0
13 Apr 2023
A Comprehensive Survey of Few-shot Learning: Evolution, Applications,
  Challenges, and Opportunities
A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities
Yisheng Song
Ting-Yuan Wang
S. Mondal
J. P. Sahoo
SLR
36
342
0
13 May 2022
Bayesian Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
Taesup Kim
Jaesik Yoon
Ousmane Amadou Dia
Sungwoong Kim
Yoshua Bengio
Sungjin Ahn
UQCV
BDL
191
498
0
11 Jun 2018
Probabilistic Model-Agnostic Meta-Learning
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn
Kelvin Xu
Sergey Levine
BDL
165
666
0
07 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
243
11,659
0
09 Mar 2017
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