Splicing learning: a novel few-shot learning approach

DOI10.1016/j.ins.2020.11.028zbMath1483.68302OpenAlexW3106624860MaRDI QIDQ2126264

Huiying Liang, Long Lu, Lianting Hu

Publication date: 14 April 2022

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.11.028

zbMATH Keywords

few-shot learningimage splicinglabel-mapping functionset organizationsplicing learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computational aspects of data analysis and big data (68T09)

Related Items (1)

Deterministic bridge regression for compressive classification

Uses Software

• CIFAR
• GitHub
• Omniglot
• STL-10 dataset
• InfoGAN

Cites Work

• A survey of randomized algorithms for training neural networks
• Human-level concept learning through probabilistic program induction

This page was built for publication: Splicing learning: a novel few-shot learning approach