554 citations · 605 across the 20 of their papers we have counts for
20 papers
A Unified Neural Network Model for Readability Assessment with Feature Projection and Length-Balanced Loss
Wenbiao Li, Ziyang Wang, Yunfang Wu
For readability assessment, traditional methods mainly employ machine learning classifiers with hundreds of linguistic features. Although the deep learning model has become the pro…
Focus-Driven Contrastive Learniang for Medical Question Summarization
Ming Zhang, Shuai Dou, Ziyang Wang +1
Automatic medical question summarization can significantly help the system to understand consumer health questions and retrieve correct answers. The Seq2Seq model based on maximum…
Triple-View Feature Learning for Medical Image Segmentation
Ziyang Wang, Irina Voiculescu
Deep learning models, e.g. supervised Encoder-Decoder style networks, exhibit promising performance in medical image segmentation, but come with a high labelling cost. We propose T…
When CNN Meet with ViT: Towards Semi-Supervised Learning for Multi-Class Medical Image Semantic Segmentation
Ziyang Wang, Tianze Li, Jian-Qing Zheng +1
Due to the lack of quality annotation in medical imaging community, semi-supervised learning methods are highly valued in image semantic segmentation tasks. In this paper, an advan…
Recursive Deformable Image Registration Network with Mutual Attention
Jian-Qing Zheng, Ziyang Wang, Baoru Huang +3
Deformable image registration, estimating the spatial transformation between different images, is an important task in medical imaging. Many previous studies have used learning-bas…
The NiuTrans Machine Translation Systems for WMT21
Shuhan Zhou, Tao Zhou, Binghao Wei +15
This paper describes NiuTrans neural machine translation systems of the WMT 2021 news translation tasks. We made submissions to 9 language directions, including English$\leftrighta…
Global Context Enhanced Graph Neural Networks for Session-based Recommendation
Ziyang Wang, Wei Wei, Gao Cong +3
Session-based recommendation (SBR) is a challenging task, which aims at recommending items based on anonymous behavior sequences. Almost all the existing solutions for SBR model us…
Atrous Residual Interconnected Encoder to Attention Decoder Framework for Vertebrae Segmentation via 3D Volumetric CT Images
Wenqiang Li, YM Tang, Ziyang Wang +2
Automatic medical image segmentation based on Computed Tomography (CT) has been widely applied for computer-aided surgery as a prerequisite. With the development of deep learning t…
Quadruple Augmented Pyramid Network for Multi-class COVID-19 Segmentation via CT
Ziyang Wang, Irina Voiculescu
COVID-19, a new strain of coronavirus disease, has been one of the most serious and infectious disease in the world. Chest CT is essential in prognostication, diagnosing this disea…
Learning Light-Weight Translation Models from Deep Transformer
Bei Li, Ziyang Wang, Hui Liu +4
Recently, deep models have shown tremendous improvements in neural machine translation (NMT). However, systems of this kind are computationally expensive and memory intensive. In t…
Exploiting Group-level Behavior Pattern forSession-based Recommendation
Ziyang Wang, Wei Wei, Xian-Ling Mao +2
Session-based recommendation (SBR) is a challenging task, which aims to predict users' future interests based on anonymous behavior sequences. Existing methods leverage powerful re…
User-based Network Embedding for Collective Opinion Spammer Detection
Ziyang Wang, Wei Wei, Xian-Ling Mao +3
Due to the huge commercial interests behind online reviews, a tremendousamount of spammers manufacture spam reviews for product reputation manipulation. To further enhance the infl…
Exploring Global Information for Session-based Recommendation
Ziyang Wang, Wei Wei, Gao Cong +4
Session-based recommendation (SBR) is a challenging task, which aims at recommending items based on anonymous behavior sequences. Most existing SBR studies model the user preferenc…
Shallow-to-Deep Training for Neural Machine Translation
Bei Li, Ziyang Wang, Hui Liu +5
Deep encoders have been proven to be effective in improving neural machine translation (NMT) systems, but training an extremely deep encoder is time consuming. Moreover, why deep m…
RAR-U-Net: a Residual Encoder to Attention Decoder by Residual Connections Framework for Spine Segmentation under Noisy Labels
Ziyang Wang, Zhengdong Zhang, Irina Voiculescu
Segmentation algorithms for medical images are widely studied for various clinical and research purposes. In this paper, we propose a new and efficient method for medical image seg…
Weight Distillation: Transferring the Knowledge in Neural Network Parameters
Ye Lin, Yanyang Li, Ziyang Wang +4
Knowledge distillation has been proven to be effective in model acceleration and compression. It allows a small network to learn to generalize in the same way as a large network. R…
Does Multi-Encoder Help? A Case Study on Context-Aware Neural Machine Translation
Bei Li, Hui Liu, Ziyang Wang +5
In encoder-decoder neural models, multiple encoders are in general used to represent the contextual information in addition to the individual sentence. In this paper, we investigat…
A Single RGB Camera Based Gait Analysis with a Mobile Tele-Robot for Healthcare
Ziyang Wang
With the increasing awareness of high-quality life, there is a growing need for health monitoring devices running robust algorithms in home environment. Health monitoring technolog…
A Novel and Efficient Tumor Detection Framework for Pancreatic Cancer via CT Images
Zhengdong Zhang, Shuai Li, Ziyang Wang +1
As Deep Convolutional Neural Networks (DCNNs) have shown robust performance and results in medical image analysis, a number of deep-learning-based tumor detection methods were deve…
Deep Learning in Medical Ultrasound Image Segmentation: a Review
Ziyang Wang
Applying machine learning technologies, especially deep learning, into medical image segmentation is being widely studied because of its state-of-the-art performance and results. I…