Search Results for author: Ruogu Fang

Found 9 papers, 5 papers with code

CADA: Multi-scale Collaborative Adversarial Domain Adaptation for Unsupervised Optic Disc and Cup Segmentation

no code implementations5 Oct 2021 Peng Liu, Charlie T. Tran, Bin Kong, Ruogu Fang

The proposed training strategy and novel unsupervised domain adaptation framework, called Collaborative Adversarial Domain Adaptation (CADA), can effectively overcome the challenge.

Unsupervised Domain Adaptation

Regression and Learning with Pixel-wise Attention for Retinal Fundus Glaucoma Segmentation and Detection

2 code implementations6 Jan 2020 Peng Liu, Ruogu Fang

In addition, we develop several attention strategies to guide the networks to learn the important features that have a major impact on prediction accuracy.

Image Restoration Using Deep Regulated Convolutional Networks

1 code implementation19 Oct 2019 Peng Liu, Xiaoxiao Zhou, Junyi Yang, El Basha Mohammad D, Ruogu Fang

While the depth of convolutional neural networks has attracted substantial attention in the deep learning research, the width of these networks has recently received greater interest.

Image Denoising Image Restoration +1

SDCNet: Smoothed Dense-Convolution Network for Restoring Low-Dose Cerebral CT Perfusion

no code implementations18 Oct 2019 Peng Liu, Ruogu Fang

With substantial public concerns on potential cancer risks and health hazards caused by the accumulated radiation exposure in medical imaging, reducing radiation dose in X-ray based medical imaging such as Computed Tomography Perfusion (CTP) has raised significant research interests.

Image Denoising

CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation

2 code implementations16 Oct 2019 Peng Liu, Bin Kong, Zhongyu Li, Shaoting Zhang, Ruogu Fang

Our proposed CFEA is an interactive paradigm which presents an exquisite of collaborative adaptation through both adversarial learning and ensembling weights.

Unsupervised Domain Adaptation

Learning Pixel-Distribution Prior with Wider Convolution for Image Denoising

1 code implementation28 Jul 2017 Peng Liu, Ruogu Fang

In this work, we explore an innovative strategy for image denoising by using convolutional neural networks (CNN) to learn pixel-distribution from noisy data.

Image Denoising

Wide Inference Network for Image Denoising via Learning Pixel-distribution Prior

2 code implementations17 Jul 2017 Peng Liu, Ruogu Fang

We explore an innovative strategy for image denoising by using convolutional neural networks (CNN) to learn similar pixel-distribution features from noisy images.

Image Denoising

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