Search Results for author: Yutong Xie

Found 22 papers, 13 papers with code

ClusTR: Exploring Efficient Self-attention via Clustering for Vision Transformers

no code implementations28 Aug 2022 Yutong Xie, Jianpeng Zhang, Yong Xia, Anton Van Den Hengel, Qi Wu

Besides, we further extend the clustering-guided attention from single-scale to multi-scale, which is conducive to dense prediction tasks.

Language Modelling

Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation

1 code implementation17 May 2022 Hexin Dong, ZiFan Chen, Mingze Yuan, Yutong Xie, Jie Zhao, Fei Yu, Bin Dong, Li Zhang

Therefore, we propose a method called region-aware metric learning (RAML), which first separates the regions of the images and generates region-aware features for further metric learning.

Few-Shot Learning Metric Learning +1

Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstruction

1 code implementation5 Mar 2022 Yutong Xie, Quanzheng Li

We propose a novel and unified method, measurement-conditioned denoising diffusion probabilistic model (MC-DDPM), for under-sampled medical image reconstruction based on DDPM.

Denoising MRI Reconstruction

Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection

1 code implementation25 Feb 2022 Ting Long, Yutong Xie, Xianyu Chen, Weinan Zhang, Qinxiang Cao, Yong Yu

We thoroughly evaluate our proposed MVG approach in the context of algorithm detection, an important and challenging subfield of PLP.

Trained Model in Supervised Deep Learning is a Conditional Risk Minimizer

1 code implementation8 Feb 2022 Yutong Xie, Dufan Wu, Bin Dong, Quanzheng Li

We proved that a trained model in supervised deep learning minimizes the conditional risk for each input (Theorem 2. 1).

Image Super-Resolution

How Much of the Chemical Space Has Been Explored? Selecting the Right Exploration Measure for Drug Discovery

no code implementations22 Dec 2021 Yutong Xie, Ziqiao Xu, Jiaqi Ma, Qiaozhu Mei

We are able to evaluate a wide range of potential exploration measures under this framework and make recommendations on existing and novel exploration measures that are suitable for the task of drug discovery.

Drug Discovery

UniMiSS: Universal Medical Self-Supervised Learning via Breaking Dimensionality Barrier

1 code implementation17 Dec 2021 Yutong Xie, Jianpeng Zhang, Yong Xia, Qi Wu

In this paper, we advocate bringing a wealth of 2D images like chest X-rays as compensation for the lack of 3D data, aiming to build a universal medical self-supervised representation learning framework, called UniMiSS.

Image Classification Medical Image Classification +2

Learning from Ambiguous Labels for Lung Nodule Malignancy Prediction

1 code implementation23 Apr 2021 Zehui Liao, Yutong Xie, Shishuai Hu, Yong Xia

According to the consistency and reliability of their annotations, we divide nodules into three sets: a consistent and reliable set (CR-Set), an inconsistent set (IC-Set), and a low reliable set (LR-Set).

CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation

1 code implementation4 Mar 2021 Yutong Xie, Jianpeng Zhang, Chunhua Shen, Yong Xia

Convolutional neural networks (CNNs) have been the de facto standard for nowadays 3D medical image segmentation.

Image Segmentation Inductive Bias +2

A General Computational Framework to Measure the Expressiveness of Complex Networks using a Tight Upper Bound of Linear Regions

no code implementations1 Jan 2021 Yutong Xie, Gaoxiang Chen, Quanzheng Li

Inspired by the proof of this upper bound and the framework of matrix computation in \citet{hinz2019framework}, we propose a general computational approach to compute a tight upper bound of regions number for theoretically any network structures (e. g. DNN with all kind of skip connections and residual structures).

A General Computational Framework to Measure the Expressiveness of Complex Networks Using a Tighter Upper Bound of Linear Regions

no code implementations8 Dec 2020 Yutong Xie, Gaoxiang Chen, Quanzheng Li

Inspired by the proof of this upper bound and theframework of matrix computation in Hinz & Van de Geer (2019), we propose ageneral computational approach to compute a tight upper bound of regions numberfor theoretically any network structures (e. g. DNN with all kind of skip connec-tions and residual structures).

Inter-slice Context Residual Learning for 3D Medical Image Segmentation

1 code implementation28 Nov 2020 Jianpeng Zhang, Yutong Xie, Yan Wang, Yong Xia

In this paper, we propose the 3D context residual network (ConResNet) for the accurate segmentation of 3D medical images.

Brain Tumor Segmentation Image Segmentation +2

PGL: Prior-Guided Local Self-supervised Learning for 3D Medical Image Segmentation

no code implementations25 Nov 2020 Yutong Xie, Jianpeng Zhang, Zehui Liao, Yong Xia, Chunhua Shen

In this paper, we propose a PriorGuided Local (PGL) self-supervised model that learns the region-wise local consistency in the latent feature space.

Image Segmentation Medical Image Segmentation +2

DoDNet: Learning to segment multi-organ and tumors from multiple partially labeled datasets

1 code implementation CVPR 2021 Jianpeng Zhang, Yutong Xie, Yong Xia, Chunhua Shen

To address this, we propose a dynamic on-demand network (DoDNet) that learns to segment multiple organs and tumors on partially labeled datasets.

Image Segmentation Medical Image Segmentation +1

Pairwise Relation Learning for Semi-supervised Gland Segmentation

no code implementations6 Aug 2020 Yutong Xie, Jianpeng Zhang, Zhibin Liao, Chunhua Shen, Johan Verjans, Yong Xia

In this paper, we propose the pairwise relation-based semi-supervised (PRS^2) model for gland segmentation on histology images.

Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly Detection

1 code implementation27 Mar 2020 Jianpeng Zhang, Yutong Xie, Guansong Pang, Zhibin Liao, Johan Verjans, Wenxin Li, Zongji Sun, Jian He, Yi Li, Chunhua Shen, Yong Xia

In this paper, we formulate the task of differentiating viral pneumonia from non-viral pneumonia and healthy controls into an one-class classification-based anomaly detection problem, and thus propose the confidence-aware anomaly detection (CAAD) model, which consists of a shared feature extractor, an anomaly detection module, and a confidence prediction module.

Anomaly Detection Classification +1

A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification

1 code implementation8 Mar 2019 Yutong Xie, Jianpeng Zhang, Yong Xia, Chunhua Shen

Our results suggest that it is possible to boost the performance of skin lesion segmentation and classification simultaneously via training a unified model to perform both tasks in a mutual bootstrapping way.

Classification General Classification +4

Visual Rhythm Prediction with Feature-Aligning Network

no code implementations29 Jan 2019 Yutong Xie, Haiyang Wang, Yan Hao, Zihao Xu

In this paper, we propose a data-driven visual rhythm prediction method, which overcomes the previous works' deficiency that predictions are made primarily by human-crafted hard rules.

Optical Flow Estimation

A Multi-Level Deep Ensemble Model for Skin Lesion Classification in Dermoscopy Images

no code implementations23 Jul 2018 Yutong Xie, Jianpeng Zhang, Yong Xia

A multi-level deep ensemble (MLDE) model that can be trained in an 'end to end' manner is proposed for skin lesion classification in dermoscopy images.

General Classification Lesion Classification +1

Classification of Medical Images and Illustrations in the Biomedical Literature Using Synergic Deep Learning

no code implementations28 Jun 2017 Jianpeng Zhang, Yong Xia, Qi Wu, Yutong Xie

The Classification of medical images and illustrations in the literature aims to label a medical image according to the modality it was produced or label an illustration according to its production attributes.

General Classification Image Classification +1

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