Cargando…
Word Embedding Distribution Propagation Graph Network for Few-Shot Learning
Few-shot learning (FSL) is of great significance to the field of machine learning. The ability to learn and generalize using a small number of samples is an obvious distinction between artificial intelligence and humans. In the FSL domain, most graph neural networks (GNNs) focus on transferring labe...
Autores principales: | Zhu, Chaoran, Wang, Ling, Han, Cheng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002792/ https://www.ncbi.nlm.nih.gov/pubmed/35408261 http://dx.doi.org/10.3390/s22072648 |
Ejemplares similares
-
FewJoint: few-shot learning for joint dialogue understanding
por: Hou, Yutai, et al.
Publicado: (2022) -
Learning few-shot imitation as cultural transmission
por: Bhoopchand, Avishkar, et al.
Publicado: (2023) -
Aesthetic Characteristics of Dance Based on Few-Shot Learning and Neural Networks
por: Qu, Dixin
Publicado: (2022) -
CLIP-Driven Prototype Network for Few-Shot Semantic Segmentation
por: Guo, Shi-Cheng, et al.
Publicado: (2023) -
Multi-Stage Meta-Learning for Few-Shot with Lie Group Network Constraint
por: Dong, Fang, et al.
Publicado: (2020)