79 citations · 187 across the 16 of their papers we have counts for
16 papers
HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk Prediction
Youru Li, Zhenfeng Zhu, Xiaobo Guo +3
Risk prediction, as a typical time series modeling problem, is usually achieved by learning trends in markers or historical behavior from sequence data, and has been widely applied…
Multi-modal Graph Learning for Disease Prediction
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu +4
Benefiting from the powerful expressive capability of graphs, graph-based approaches have been popularly applied to handle multi-modal medical data and achieved impressive performa…
Multi-modal Graph Learning for Disease Prediction
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu +3
Benefiting from the powerful expressive capability of graphs, graph-based approaches have achieved impressive performance in various biomedical applications. Most existing methods…
Margin Preserving Self-paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation
Zhizhe Liu, Zhenfeng Zhu, Shuai Zheng +3
To bridge the gap between the source and target domains in unsupervised domain adaptation (UDA), the most common strategy puts focus on matching the marginal distributions in the f…
Adversarial Graph Disentanglement
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu +2
A real-world graph has a complex topological structure, which is often formed by the interaction of different latent factors. However, most existing methods lack consideration of t…
LID 2020: The Learning from Imperfect Data Challenge Results
Yunchao Wei, Shuai Zheng, Ming-Ming Cheng +32
Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotate…
Taking Modality-free Human Identification as Zero-shot Learning
Zhizhe Liu, Xingxing Zhang, Zhenfeng Zhu +3
Human identification is an important topic in event detection, person tracking, and public security. There have been numerous methods proposed for human identification, such as fac…
From Anchor Generation to Distribution Alignment: Learning a Discriminative Embedding Space for Zero-Shot Recognition
Fuzhen Li, Zhenfeng Zhu, Xingxing Zhang +2
In zero-shot learning (ZSL), the samples to be classified are usually projected into side information templates such as attributes. However, the irregular distribution of templates…
ProLFA: Representative Prototype Selection for Local Feature Aggregation
Xingxing Zhang, Zhenfeng Zhu, Yao Zhao
Given a set of hand-crafted local features, acquiring a global representation via aggregation is a promising technique to boost computational efficiency and improve task performanc…
Hierarchical Prototype Learning for Zero-Shot Recognition
Xingxing Zhang, Shupeng Gui, Zhenfeng Zhu +2
Zero-Shot Learning (ZSL) has received extensive attention and successes in recent years especially in areas of fine-grained object recognition, retrieval, and image captioning. Key…
ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries
Xingxing Zhang, Shupeng Gui, Zhenfeng Zhu +2
Zero-shot learning (ZSL) has received extensive attention recently especially in areas of fine-grained object recognition, retrieval, and image captioning. Due to the complete lack…
Convolutional Prototype Learning for Zero-Shot Recognition
Zhizhe Liu, Xingxing Zhang, Zhenfeng Zhu +3
Zero-shot learning (ZSL) has received increasing attention in recent years especially in areas of fine-grained object recognition, retrieval, and image captioning. The key to ZSL i…
Edge Heuristic GAN for Non-uniform Blind Deblurring
Shuai Zheng, Zhenfeng Zhu, Jian Cheng +2
Non-uniform blur, mainly caused by camera shake and motions of multiple objects, is one of the most common causes of image quality degradation. However, the traditional blind deblu…
EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction
Youru Li, Zhenfeng Zhu, Deqiang Kong +2
Time series prediction with deep learning methods, especially long short-term memory neural networks (LSTMs), have scored significant achievements in recent years. Despite the fact…
A New Evaluation Protocol and Benchmarking Results for Extendable Cross-media Retrieval
Ruoyu Liu, Yao Zhao, Liang Zheng +2
This paper proposes a new evaluation protocol for cross-media retrieval which better fits the real-word applications. Both image-text and text-image retrieval modes are considered.…
Camera Fingerprint: A New Perspective for Identifying User's Identity
Xiang Jiang, Shikui Wei, Ruizhen Zhao +2
Identifying user's identity is a key problem in many data mining applications, such as product recommendation, customized content delivery and criminal identification. Given a set…