6 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CV2020★ 2 cited
High-order structure preserving graph neural network for few-shot learning
Guangfeng Lin, Ying Yang, Yindi Fan +3
Few-shot learning can find the latent structure information between the prior knowledge and the queried data by the similarity metric of meta-learning to construct the discriminati…
cs.CV2020
Deep graph learning for semi-supervised classification
Guangfeng Lin, Xiaobing Kang, Kaiyang Liao +2
Graph learning (GL) can dynamically capture the distribution structure (graph structure) of data based on graph convolutional networks (GCN), and the learning quality of the graph…
cs.CV2019★ 6 cited
Transfer feature generating networks with semantic classes structure for zero-shot learning
Guangfeng Lin, Wanjun Chen, Kaiyang Liao +2
Feature generating networks face to the most important question, which is the fitting difference (inconsistence) of the distribution between the generated feature and the real data…