Search Results for author: Ke Yan

Found 47 papers, 18 papers with code

Inferring from References with Differences for Semi-Supervised Node Classification on Graphs

1 code implementation Mathematics 2022 Yi Luo, Guangchun Luo, Ke Yan, Aiguo Chen

Following the application of Deep Learning to graphic data, Graph Neural Networks (GNNs) have become the dominant method for Node Classification on graphs in recent years.

Node Classification

Expanding Low-Density Latent Regions for Open-Set Object Detection

1 code implementation28 Mar 2022 Jiaming Han, Yuqiang Ren, Jian Ding, Xingjia Pan, Ke Yan, Gui-Song Xia

Thus, unknown objects in low-density regions can be easily identified with the learned unknown probability.

Contrastive Learning Object Detection

Accurate and Generalizable Quantitative Scoring of Liver Steatosis from Ultrasound Images via Scalable Deep Learning

no code implementations12 Oct 2021 Bowen Li, Dar-In Tai, Ke Yan, Yi-Cheng Chen, Shiu-Feng Huang, Tse-Hwa Hsu, Wan-Ting Yu, Jing Xiao, Le Lu, Adam P. Harrison

High diagnostic performance was observed across all viewpoints: area under the curves of the ROC to classify >=mild, >=moderate, =severe steatosis grades were 0. 85, 0. 90, and 0. 93, respectively.

Transformer-based Dual Relation Graph for Multi-label Image Recognition

no code implementations ICCV 2021 Jiawei Zhao, Ke Yan, Yifan Zhao, Xiaowei Guo, Feiyue Huang, Jia Li

Different from these researches, in this paper, we propose a novel Transformer-based Dual Relation learning framework, constructing complementary relationships by exploring two aspects of correlation, i. e., structural relation graph and semantic relation graph.

Heterogeneous Relational Complement for Vehicle Re-identification

1 code implementation ICCV 2021 Jiajian Zhao, Yifan Zhao, Jia Li, Ke Yan, Yonghong Tian

The crucial problem in vehicle re-identification is to find the same vehicle identity when reviewing this object from cross-view cameras, which sets a higher demand for learning viewpoint-invariant representations.

Vehicle Re-Identification

Discriminator-Free Generative Adversarial Attack

1 code implementation20 Jul 2021 ShaoHao Lu, Yuqiao Xian, Ke Yan, Yi Hu, Xing Sun, Xiaowei Guo, Feiyue Huang, Wei-Shi Zheng

The Deep Neural Networks are vulnerable toadversarial exam-ples(Figure 1), making the DNNs-based systems collapsed byadding the inconspicuous perturbations to the images.

Adversarial Attack Disentanglement

Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages

2 code implementations16 Jun 2021 Yi Luo, Aiguo Chen, Ke Yan, Ling Tian

Nowadays, Graph Neural Networks (GNNs) following the Message Passing paradigm become the dominant way to learn on graphic data.

Node Classification

Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection

no code implementations5 May 2021 YouBao Tang, Ke Yan, Jinzheng Cai, Lingyun Huang, Guotong Xie, Jing Xiao, JingJing Lu, Gigin Lin, Le Lu

PDNet learns comprehensive and representative deep image features for our tasks and produces more accurate results on both lesion segmentation and RECIST diameter prediction.

Lesion Segmentation

Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss

no code implementations3 May 2021 YouBao Tang, Jinzheng Cai, Ke Yan, Lingyun Huang, Guotong Xie, Jing Xiao, JingJing Lu, Gigin Lin, Le Lu

Accurately segmenting a variety of clinically significant lesions from whole body computed tomography (CT) scans is a critical task on precision oncology imaging, denoted as universal lesion segmentation (ULS).

Computed Tomography (CT) Lesion Segmentation +1

Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings

no code implementations12 Apr 2021 Bowen Li, Xinping Ren, Ke Yan, Le Lu, Lingyun Huang, Guotong Xie, Jing Xiao, Dar-In Tai, Adam P. Harrison

Importantly, ADDLE does not expect multiple raters per image in training, meaning it can readily learn from data mined from hospital archives.

Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining

no code implementations9 Mar 2021 Jieneng Chen, Ke Yan, Yu-Dong Zhang, YouBao Tang, Xun Xu, Shuwen Sun, Qiuping Liu, Lingyun Huang, Jing Xiao, Alan L. Yuille, Ya zhang, Le Lu

(2) The sampled deep vertex features with positional embedding are mapped into a sequential space and decoded by a multilayer perceptron (MLP) for semantic classification.

Memory-Associated Differential Learning

2 code implementations10 Feb 2021 Yi Luo, Aiguo Chen, Bei Hui, Ke Yan

Conventional Supervised Learning approaches focus on the mapping from input features to output labels.

Link Prediction

Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies

1 code implementation CVPR 2021 Jinzheng Cai, YouBao Tang, Ke Yan, Adam P. Harrison, Jing Xiao, Gigin Lin, Le Lu

In this work, we present deep lesion tracker (DLT), a deep learning approach that uses both appearance- and anatomical-based signals.

3D Object Tracking

Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT

1 code implementation5 Sep 2020 Ke Yan, Jinzheng Cai, Youjing Zheng, Adam P. Harrison, Dakai Jin, YouBao Tang, Yuxing Tang, Lingyun Huang, Jing Xiao, Le Lu

For example, DeepLesion is such a large-scale CT image dataset with lesions of various types, but it also has many unlabeled lesions (missing annotations).

Lesion Detection Transfer Learning

Deep Volumetric Universal Lesion Detection using Light-Weight Pseudo 3D Convolution and Surface Point Regression

no code implementations30 Aug 2020 Jinzheng Cai, Ke Yan, Chi-Tung Cheng, Jing Xiao, Chien-Hung Liao, Le Lu, Adam P. Harrison

Identifying, measuring and reporting lesions accurately and comprehensively from patient CT scans are important yet time-consuming procedures for physicians.

Lesion Detection

Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network

no code implementations29 Aug 2020 Chun-Hung Chao, Zhuotun Zhu, Dazhou Guo, Ke Yan, Tsung-Ying Ho, Jinzheng Cai, Adam P. Harrison, Xianghua Ye, Jing Xiao, Alan Yuille, Min Sun, Le Lu, Dakai Jin

Specifically, we first utilize a 3D convolutional neural network with ROI-pooling to extract the GTV$_{LN}$'s instance-wise appearance features.

Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-based Gating using 3D CT/PET Imaging in Radiotherapy

no code implementations27 Aug 2020 Zhuotun Zhu, Dakai Jin, Ke Yan, Tsung-Ying Ho, Xianghua Ye, Dazhou Guo, Chun-Hung Chao, Jing Xiao, Alan Yuille, Le Lu

Finding, identifying and segmenting suspicious cancer metastasized lymph nodes from 3D multi-modality imaging is a clinical task of paramount importance.

CFAD: Coarse-to-Fine Action Detector for Spatiotemporal Action Localization

no code implementations ECCV 2020 Yuxi Li, Weiyao Lin, John See, Ning Xu, Shugong Xu, Ke Yan, Cong Yang

Most current pipelines for spatio-temporal action localization connect frame-wise or clip-wise detection results to generate action proposals, where only local information is exploited and the efficiency is hindered by dense per-frame localization.

Action Detection Frame +2

One Click Lesion RECIST Measurement and Segmentation on CT Scans

no code implementations21 Jul 2020 Youbao Tang, Ke Yan, Jing Xiao, Ranold M. Summers

Based on the results of the first network, the second one refines the lesion segmentation and RECIST estimation.

Lesion Segmentation

Universal Lesion Detection by Learning from Multiple Heterogeneously Labeled Datasets

no code implementations28 May 2020 Ke Yan, Jinzheng Cai, Adam P. Harrison, Dakai Jin, Jing Xiao, Le Lu

First, we learn a multi-head multi-task lesion detector using all datasets and generate lesion proposals on DeepLesion.

Ranked #3 on Medical Object Detection on DeepLesion (using extra training data)

Lesion Detection Medical Object Detection +1

Detecting Scatteredly-Distributed, Small, andCritically Important Objects in 3D OncologyImaging via Decision Stratification

no code implementations27 May 2020 Zhuotun Zhu, Ke Yan, Dakai Jin, Jinzheng Cai, Tsung-Ying Ho, Adam P. Harrison, Dazhou Guo, Chun-Hung Chao, Xianghua Ye, Jing Xiao, Alan Yuille, Le Lu

We focus on the detection and segmentation of oncology-significant (or suspicious cancer metastasized) lymph nodes (OSLNs), which has not been studied before as a computational task.

Lesion Harvester: Iteratively Mining Unlabeled Lesions and Hard-Negative Examples at Scale

1 code implementation21 Jan 2020 Jinzheng Cai, Adam P. Harrison, Youjing Zheng, Ke Yan, Yuankai Huo, Jing Xiao, Lin Yang, Le Lu

This is the goal of our work, where we develop a powerful system to harvest missing lesions from the DeepLesion dataset at high precision.

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

13 code implementations12 Aug 2019 Ke Yan, You-Bao Tang, Yifan Peng, Veit Sandfort, Mohammadhadi Bagheri, Zhiyong Lu, Ronald M. Summers

When reading medical images such as a computed tomography (CT) scan, radiologists generally search across the image to find lesions, characterize and measure them, and then describe them in the radiological report.

Computed Tomography (CT) Lesion Detection +2

A self-attention based deep learning method for lesion attribute detection from CT reports

no code implementations30 Apr 2019 Yifan Peng, Ke Yan, Veit Sandfort, Ronald M. Summers, Zhiyong Lu

In radiology, radiologists not only detect lesions from the medical image, but also describe them with various attributes such as their type, location, size, shape, and intensity.

Fine-grained lesion annotation in CT images with knowledge mined from radiology reports

no code implementations4 Mar 2019 Ke Yan, Yifan Peng, Zhiyong Lu, Ronald M. Summers

To address this problem, we define a set of 145 labels based on RadLex to describe a large variety of lesions in the DeepLesion dataset.

ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example Mining

1 code implementation18 Jan 2019 Youbao Tang, Ke Yan, Yu-Xing Tang, Jiamin Liu, Jing Xiao, Ronald M. Summers

To address this problem, this work constructs a pseudo mask for each lesion region that can be considered as a surrogate of the real mask, based on which the Mask R-CNN is employed for lesion detection.

Computed Tomography (CT) Lesion Detection

Attention Driven Person Re-identification

no code implementations13 Oct 2018 Fan Yang, Ke Yan, Shijian Lu, Huizhu Jia, Xiaodong Xie, Wen Gao

Person re-identification (ReID) is a challenging task due to arbitrary human pose variations, background clutters, etc.

Person Re-Identification

Deep Learning for Image Denoising: A Survey

no code implementations11 Oct 2018 Chunwei Tian, Yong Xu, Lunke Fei, Ke Yan

Since the proposal of big data analysis and Graphic Processing Unit (GPU), the deep learning technology has received a great deal of attention and has been widely applied in the field of imaging processing.

Image Denoising

CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement

no code implementations18 Jul 2018 Youbao Tang, Jinzheng Cai, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers

The first GAN reduces the noise in the CT image and the second GAN generates a higher resolution image with enhanced boundaries and high contrast.

Computed Tomography (CT) Image Enhancement +2

Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST

no code implementations25 Jan 2018 Jinzheng Cai, You-Bao Tang, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers

Toward this end, we introduce a convolutional neural network based weakly supervised self-paced segmentation (WSSS) method to 1) generate the initial lesion segmentation on the axial RECIST-slice; 2) learn the data distribution on RECIST-slices; 3) adapt to segment the whole volume slice by slice to finally obtain a volumetric segmentation.

Lesion Segmentation Super-Resolution

Information Design in Crowdfunding under Thresholding Policies

no code implementations12 Sep 2017 Wen Shen, Jacob W. Crandall, Ke Yan, Cristina V. Lopes

We introduce a heuristic algorithm to dynamically compute information-disclosure policies for the entrepreneur, followed by an empirical evaluation to demonstrate its competitiveness over the widely-adopted immediate-disclosure policy.

Learning a Repression Network for Precise Vehicle Search

1 code implementation8 Aug 2017 Qiantong Xu, Ke Yan, Yonghong Tian

The growing explosion in the use of surveillance cameras in public security highlights the importance of vehicle search from large-scale image databases.

Multi-Task Learning

Unsupervised Body Part Regression via Spatially Self-ordering Convolutional Neural Networks

2 code implementations12 Jul 2017 Ke Yan, Le Lu, Ronald M. Summers

In this paper, we propose a convolutional neural network (CNN) based Unsupervised Body part Regression (UBR) algorithm to address this problem.

Anomaly Detection

Local Multiple Directional Pattern of Palmprint Image

no code implementations21 Jul 2016 Lunke Fei, Jie Wen, Zheng Zhang, Ke Yan, Zuofeng Zhong

Conventional methods usually capture the only one of the most dominant direction of palmprint images.

Learning Domain-Invariant Subspace using Domain Features and Independence Maximization

2 code implementations15 Mar 2016 Ke Yan, Lu Kou, David Zhang

In this paper, we focus on the problem of instrumental variation and time-varying drift in the field of sensors and measurement, which can be viewed as discrete and continuous distributional change in the feature space.

Domain Adaptation

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