9 citations · 25 across the 16 of their papers we have counts for
5 papers · 1 filter
Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning
Zhe Liu, Yun Li, Lina Yao +2
Current approaches to Zero-Shot Learning (ZSL) struggle to learn generalizable semantic knowledge capable of capturing complex correlations. Inspired by \emph{Spiral Curriculum}, w…
An Entropy-guided Reinforced Partial Convolutional Network for Zero-Shot Learning
Yun Li, Zhe Liu, Lina Yao +3
Zero-Shot Learning (ZSL) aims to transfer learned knowledge from observed classes to unseen classes via semantic correlations. A promising strategy is to learn a global-local repre…
Attribute-Modulated Generative Meta Learning for Zero-Shot Classification
Yun Li, Zhe Liu, Lina Yao +1
Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to semantically related unseen classes, which are absent during training. The promising strategies for ZSL are…
Task Aligned Generative Meta-learning for Zero-shot Learning
Zhe Liu, Yun Li, Lina Yao +2
Zero-shot learning (ZSL) refers to the problem of learning to classify instances from the novel classes (unseen) that are absent in the training set (seen). Most ZSL methods infer…
Generative Adversarial U-Net for Domain-free Medical Image Augmentation
Xiaocong Chen, Yun Li, Lina Yao +2
The shortage of annotated medical images is one of the biggest challenges in the field of medical image computing. Without a sufficient number of training samples, deep learning ba…