Search Results for author: Xi Yang

Found 30 papers, 6 papers with code

Tensorial tomographic differential phase-contrast microscopy

no code implementations25 Apr 2022 Shiqi Xu, Xiang Dai, Xi Yang, Kevin C. Zhou, Kanghyun Kim, Vinayak Pathak, Carolyn Glass, Roarke Horstmeyer

We report Tensorial Tomographic Differential Phase-Contrast microscopy (T2DPC), a quantitative label-free tomographic imaging method for simultaneous measurement of phase and anisotropy.

From 2D Images to 3D Model:Weakly Supervised Multi-View Face Reconstruction with Deep Fusion

no code implementations8 Apr 2022 Weiguang Zhao, Chaolong Yang, Jianan Ye, Yuyao Yan, Xi Yang, Kaizhu Huang

We consider the problem of Multi-view 3D Face Reconstruction (MVR) with weakly supervised learning that leverages a limited number of 2D face images (e. g. 3) to generate a high-quality 3D face model with very light annotation.

3D Face Reconstruction Face Model

Towards Semi-Supervised Deep Facial Expression Recognition with An Adaptive Confidence Margin

1 code implementation23 Mar 2022 Hangyu Li, Nannan Wang, Xi Yang, Xiaoyu Wang, Xinbo Gao

In this paper, we learn an Adaptive Confidence Margin (Ada-CM) to fully leverage all unlabeled data for semi-supervised deep facial expression recognition.

Facial Expression Recognition

A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift

1 code implementation17 Mar 2022 Shi Guo, Xi Yang, jianqi ma, Gaofeng Ren, Lei Zhang

Denoising and demosaicking are two essential steps to reconstruct a clean full-color image from the raw data.

Demosaicking Denoising +1

GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records

no code implementations2 Feb 2022 Xi Yang, Nima PourNejatian, Hoo Chang Shin, Kaleb E Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Mona G Flores, Ying Zhang, Tanja Magoc, Christopher A Harle, Gloria Lipori, Duane A Mitchell, William R Hogan, Elizabeth A Shenkman, Jiang Bian, Yonghui Wu

We developed GatorTron models from scratch using the BERT architecture of different sizes including 345 million, 3. 9 billion, and 8. 9 billion parameters, compared GatorTron with three existing transformer models in the clinical and biomedical domain on 5 different clinical NLP tasks including clinical concept extraction, relation extraction, semantic textual similarity, natural language inference, and medical question answering, to examine how large transformer models could help clinical NLP at different linguistic levels.

Clinical Concept Extraction Language Modelling +4

Generalised Image Outpainting with U-Transformer

no code implementations27 Jan 2022 Penglei Gao, Xi Yang, Rui Zhang, Kaizhu Huang, Yujie Geng, Yuyao Yan

While most present image outpainting conducts horizontal extrapolation, we study the generalised image outpainting problem that extrapolates visual context all-side around a given image.

Image Outpainting

Tracing Text Provenance via Context-Aware Lexical Substitution

no code implementations15 Dec 2021 Xi Yang, Jie Zhang, Kejiang Chen, Weiming Zhang, Zehua Ma, Feng Wang, Nenghai Yu

Tracing text provenance can help claim the ownership of text content or identify the malicious users who distribute misleading content like machine-generated fake news.

Optical Character Recognition

A Study of Social and Behavioral Determinants of Health in Lung Cancer Patients Using Transformers-based Natural Language Processing Models

no code implementations10 Aug 2021 Zehao Yu, Xi Yang, Chong Dang, Songzi Wu, Prakash Adekkanattu, Jyotishman Pathak, Thomas J. George, William R. Hogan, Yi Guo, Jiang Bian, Yonghui Wu

In this study, we examined two state-of-the-art transformer-based NLP models, including BERT and RoBERTa, to extract SBDoH concepts from clinical narratives, applied the best performing model to extract SBDoH concepts on a lung cancer screening patient cohort, and examined the difference of SBDoH information between NLP extracted results and structured EHRs (SBDoH information captured in standard vocabularies such as the International Classification of Diseases codes).

Clinical Relation Extraction Using Transformer-based Models

1 code implementation19 Jul 2021 Xi Yang, Zehao Yu, Yi Guo, Jiang Bian, Yonghui Wu

The goal of this study is to systematically explore three widely used transformer-based models (i. e., BERT, RoBERTa, and XLNet) for clinical relation extraction and develop an open-source package with clinical pre-trained transformer-based models to facilitate information extraction in the clinical domain.

Classification Multi-class Classification +1

Part2Word: Learning Joint Embedding of Point Clouds and Text by Matching Parts to Words

no code implementations5 Jul 2021 Chuan Tang, Xi Yang, Bojian Wu, Zhizhong Han, Yi Chang

To resolve this issue, we propose a method to learn joint embedding of point clouds and text by matching parts from shapes to words from sentences in a common space.

Text Matching

Sketch-based Normal Map Generation with Geometric Sampling

no code implementations23 Apr 2021 Yi He, Haoran Xie, Chao Zhang, Xi Yang, Kazunori Miyata

This paper proposes a deep generative model for generating normal maps from users sketch with geometric sampling.

Brain Surface Reconstruction from MRI Images Based on Segmentation Networks Applying Signed Distance Maps

no code implementations9 Apr 2021 Heng Fang, Xi Yang, Taichi Kin, Takeo Igarashi

Whole-brain surface extraction is an essential topic in medical imaging systems as it provides neurosurgeons with a broader view of surgical planning and abnormality detection.

Anomaly Detection Skull Stripping +1

Visual High Dimensional Hypothesis Testing

1 code implementation2 Jan 2021 Xi Yang, Jan Hannig, J. S. Marron

In exploratory data analysis of known classes of high dimensional data, a central question is how distinct are the classes?

Syncretic Modality Collaborative Learning for Visible Infrared Person Re-Identification

no code implementations ICCV 2021 Ziyu Wei, Xi Yang, Nannan Wang, Xinbo Gao

Visible infrared person re-identification (VI-REID) aims to match pedestrian images between the daytime visible and nighttime infrared camera views.

Person Re-Identification

Real-World Video Super-Resolution: A Benchmark Dataset and a Decomposition Based Learning Scheme

1 code implementation ICCV 2021 Xi Yang, Wangmeng Xiang, Hui Zeng, Lei Zhang

Existing VSR methods are mostly trained and evaluated on synthetic datasets, where the LR videos are uniformly downsampled from their high-resolution (HR) counterparts by some simple operators (e. g., bicubic downsampling).

Video Super-Resolution

Sparse Array of Sub-surface Aided Anti-blockage mmWave Communication Systems

no code implementations3 Dec 2020 Weicong Chen, Xi Yang, Shi Jin, Pingping Xu

An approximated ergodic spectral efficiency of the SAoS aided system is derived and the performance impact of the SAoS design is evaluated.

Information Theory Information Theory

Explainable Tensorized Neural Ordinary Differential Equations forArbitrary-step Time Series Prediction

no code implementations26 Nov 2020 Penglei Gao, Xi Yang, Rui Zhang, Kaizhu Huang

We propose a continuous neural network architecture, termed Explainable Tensorized Neural Ordinary Differential Equations (ETN-ODE), for multi-step time series prediction at arbitrary time points.

Time Series Time Series Prediction

Towards Dynamic Urban Bike Usage Prediction for Station Network Reconfiguration

no code implementations13 Aug 2020 Xi Yang, Suining He

To fill this gap, in this work we propose a novel and efficient bike station-level prediction algorithm called AtCoR, which can predict the bike usage at both existing and new stations (candidate locations during reconfiguration).

Improved Preterm Prediction Based on Optimized Synthetic Sampling of EHG Signal

no code implementations3 Jul 2020 Jinshan Xu, Zhenqin Chen, Yanpei Lu, Xi Yang, Alain Pumir

Preterm labor is the leading cause of neonatal morbidity and mortality and has attracted research efforts from many scientific areas.

A Two-step Surface-based 3D Deep Learning Pipeline for Segmentation of Intracranial Aneurysms

no code implementations29 Jun 2020 Xi Yang, Ding Xia, Taichi Kin, Takeo Igarashi

In this study, we offer a two-step surface-based deep learning pipeline that achieves significantly higher performance.

Medical Diagnosis

Underwater image enhancement with Image Colorfulness Measure

no code implementations18 Apr 2020 Hui Li, Xi Yang, ZhenMing Li, TianLun Zhang

To improve the visual quality of underwater images, we proposed a novel enhancement model, which is a trainable end-to-end neural model.

Image Enhancement

DL-based CSI Feedback and Cooperative Recovery in Massive MIMO

no code implementations6 Mar 2020 Jiajia Guo, Xi Yang, Chao-Kai Wen, Shi Jin, Geoffrey Ye Li

In this paper, we exploit the correlation between nearby user equipment (UE) and develop a deep learning-based channel state information (CSI) feedback and cooperative recovery framework, CoCsiNet, to reduce the feedback overhead.

Information Theory Signal Processing Information Theory

IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning

1 code implementation CVPR 2020 Xi Yang, Ding Xia, Taichi Kin, Takeo Igarashi

In this paper, instead of 2D medical images, we introduce an open-access 3D intracranial aneurysm dataset, IntrA, that makes the application of points-based and mesh-based classification and segmentation models available.

General Classification Surface Reconstruction

G2MF-WA: Geometric Multi-Model Fitting with Weakly Annotated Data

no code implementations20 Jan 2020 Chao Zhang, Xuequan Lu, Katsuya Hotta, Xi Yang

The WA data can be naturally obtained in an interactive way for specific tasks, for example, in the case of homography estimation, one can easily annotate points on the same plane/object with a single label by observing the image.

Homography Estimation

Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods

no code implementations1 Oct 2019 Xi Yang, Yan Gong, Nida Waheed, Keith March, Jiang Bian, William R. Hogan, Yonghui Wu

Early detection of cancer patients at risk for cardiotoxicity before cardiotoxic treatments and providing preventive measures are potential solutions to improve cancer patients's quality of life.

G-SMOTE: A GMM-based synthetic minority oversampling technique for imbalanced learning

no code implementations24 Oct 2018 Tianlun Zhang, Xi Yang

In this paper, the focus is to develop a robust synthetic minority oversampling technique which falls the umbrella of data level approaches.

Saliency deep embedding for aurora image search

no code implementations23 May 2018 Xi Yang, Xinbo Gao, Bin Song, Nannan Wang, Dong Yang

In this paper, we aim to explore a new search method for images captured with circular fisheye lens, especially the aurora images.

Image Retrieval Region Proposal

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