4 citations · 4 across the 1 of their papers we have counts for
3 papers
cs.LG2019
Structure fusion based on graph convolutional networks for semi-supervised classification
Guangfeng Lin, Jing Wang, Kaiyang Liao +2
Suffering from the multi-view data diversity and complexity for semi-supervised classification, most of existing graph convolutional networks focus on the networks architecture con…
cs.CV2019
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…
cs.CV2018★ 4 cited
Class label autoencoder for zero-shot learning
Guangfeng Lin, Caixia Fan, Wanjun Chen +2
Existing zero-shot learning (ZSL) methods usually learn a projection function between a feature space and a semantic embedding space(text or attribute space) in the training seen c…