A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities

Baby steps towards few-shot learning with multiple semantics

(2022) Eli Schwartz et al.   PATTERN RECOGNITION LETTERS

Few-shot learning based on Attn-CutMix and task-adaptive transformer for the recognition of cotton growth state

(2022) Yuhang Huang et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

SelfNet: A semi-supervised local Fisher discriminant network for few-shot learning

(2022) Rui Feng et al.   NEUROCOMPUTING

ReNAP: Relation network with adaptiveprototypical learning for few-shot classification

(2022) Xiaoxu Li et al.   NEUROCOMPUTING

MGML: Momentum group meta-learning for few-shot image classification

(2022) Xiaomeng Zhu et al.   NEUROCOMPUTING

SaberNet: Self-attention based effective relation network for few-shot learning

(2022) Zijun Li et al.   PATTERN RECOGNITION

PFEMed: Few-shot medical image classification using prior guided feature enhancement

(2022) Zhiyong Dai et al.   PATTERN RECOGNITION

SAPENet: Self-Attention based Prototype Enhancement Network for Few-shot Learning

(2022) Xilang Huang et al.   PATTERN RECOGNITION

Revisiting metric learning for few-shot image classification

(2020) Xiaomeng Li et al.   NEUROCOMPUTING

Deep transductive network for generalized zero shot learning

(2020) Haofeng Zhang et al.   PATTERN RECOGNITION

Generalizing from a Few Examples

(2020) Yaqing Wang et al.   ACM COMPUTING SURVEYS

A Comprehensive Survey on Graph Neural Networks

(2020) Zonghan Wu et al.   IEEE Transactions on Neural Networks and Learning Systems

Prior Guided Feature Enrichment Network for Few-Shot Segmentation

(2020) Zhuotao Tian et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

The Omniglot challenge: a 3-year progress report

(2019) Brenden M Lake et al.   Current Opinion in Behavioral Sciences