9 citations · 14 across the 6 of their papers we have counts for
6 papers
Simple Primitives with Feasibility- and Contextuality-Dependence for Open-World Compositional Zero-shot Learning
Zhe Liu, Yun Li, Lina Yao +4
The task of Compositional Zero-Shot Learning (CZSL) is to recognize images of novel state-object compositions that are absent during the training stage. Previous methods of learnin…
Side-aware Meta-Learning for Cross-Dataset Listener Diagnosis with Subjective Tinnitus
Yun Li, Zhe Liu, Lina Yao +3
With the development of digital technology, machine learning has paved the way for the next generation of tinnitus diagnoses. Although machine learning has been widely applied in E…
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…
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…
Agglomerative Neural Networks for Multi-view Clustering
Zhe Liu, Yun Li, Lina Yao +2
Conventional multi-view clustering methods seek for a view consensus through minimizing the pairwise discrepancy between the consensus and subviews. However, the pairwise compariso…