Search Results for author: Jianpeng Zhang

Found 19 papers, 8 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

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

Domain and Content Adaptive Convolution based Multi-Source Domain Generalization for Medical Image Segmentation

1 code implementation13 Sep 2021 Shishuai Hu, Zehui Liao, Jianpeng Zhang, Yong Xia

In the DAC module, a dynamic convolutional head is conditioned on the predicted domain code of the input to make our model adapt to the unseen target domain.

Domain Generalization Image Segmentation +3

Kernel Adversarial Learning for Real-world Image Super-resolution

no code implementations19 Apr 2021 Hu Wang, Congbo Ma, Jianpeng Zhang, Gustavo Carneiro

Current deep image super-resolution (SR) approaches attempt to restore high-resolution images from down-sampled images or by assuming degradation from simple Gaussian kernels and additive noises.

Image Super-Resolution

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

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 Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification

no code implementations17 Aug 2019 Yang Liu, Jianpeng Zhang, Chao GAO, Jinghua Qu, Lixin Ji

In this paper, we investigate the effect of different hyperparameters as well as different combinations of hyperparameters settings on the performance of the Attention-Gated Convolutional Neural Networks (AGCNNs), e. g., the kernel window size, the number of feature maps, the keep rate of the dropout layer, and the activation function.

General Classification Sentence Classification

Natural-Logarithm-Rectified Activation Function in Convolutional Neural Networks

no code implementations10 Aug 2019 Yang Liu, Jianpeng Zhang, Chao GAO, Jinghua Qu, Lixin Ji

Activation functions play a key role in providing remarkable performance in deep neural networks, and the rectified linear unit (ReLU) is one of the most widely used activation functions.

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

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

struc2gauss: Structural Role Preserving Network Embedding via Gaussian Embedding

no code implementations25 May 2018 Yulong Pei, Xin Du, Jianpeng Zhang, George Fletcher, Mykola Pechenizkiy

Almost all previous methods represent a node into a point in space and focus on local structural information, i. e., neighborhood information.

Network Embedding

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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