4 citations · 6 across the 5 of their papers we have counts for
5 papers
Zero-Shot Learning Based on Knowledge Sharing
Zeng Ting, Xiang Hongxin, Xie Cheng +2
Zero-Shot Learning (ZSL) is an emerging research that aims to solve the classification problems with very few training data. The present works on ZSL mainly focus on the mapping of…
Class Knowledge Overlay to Visual Feature Learning for Zero-Shot Image Classification
Cheng Xie, Ting Zeng, Hongxin Xiang +3
New categories can be discovered by transforming semantic features into synthesized visual features without corresponding training samples in zero-shot image classification. Althou…
Multi-Knowledge Fusion for New Feature Generation in Generalized Zero-Shot Learning
Hongxin Xiang, Cheng Xie, Ting Zeng +1
Suffering from the semantic insufficiency and domain-shift problems, most of existing state-of-the-art methods fail to achieve satisfactory results for Zero-Shot Learning (ZSL). In…
Cross Knowledge-based Generative Zero-Shot Learning Approach with Taxonomy Regularization
Cheng Xie, Hongxin Xiang, Ting Zeng +3
Although zero-shot learning (ZSL) has an inferential capability of recognizing new classes that have never been seen before, it always faces two fundamental challenges of the cross…
MFL_COVID19: Quantifying Country-based Factors affecting Case Fatality Rate in Early Phase of COVID-19 Epidemic via Regularised Multi-task Feature Learning
Po Yang, Jun Qi, Xulong Wang +1
Recent outbreak of COVID-19 has led a rapid global spread around the world. Many countries have implemented timely intensive suppression to minimize the infections, but resulted in…