Search Results for author: Chao Ren

Found 6 papers, 2 papers with code

Adaptive Consistency Prior Based Deep Network for Image Denoising

1 code implementation CVPR 2021 Chao Ren, Xiaohai He, Chuncheng Wang, Zhibo Zhao

To solve this problem, we propose a novel model-based denoising method to inform the design of our denoising network.

Image Denoising

Multi-resolution Outlier Pooling for Sorghum Classification

no code implementations10 Jun 2021 Chao Ren, Justin Dulay, Gregory Rolwes, Duke Pauli, Nadia Shakoor, Abby Stylianou

Automated high throughput plant phenotyping involves leveraging sensors, such as RGB, thermal and hyperspectral cameras (among others), to make large scale and rapid measurements of the physical properties of plants for the purpose of better understanding the difference between crops and facilitating rapid plant breeding programs.

Classification

Real-World Single Image Super-Resolution: A Brief Review

1 code implementation3 Mar 2021 Honggang Chen, Xiaohai He, Linbo Qing, Yuanyuan Wu, Chao Ren, Ce Zhu

More specifically, this review covers the critical publically available datasets and assessment metrics for RSISR, and four major categories of RSISR methods, namely the degradation modeling-based RSISR, image pairs-based RSISR, domain translation-based RSISR, and self-learning-based RSISR.

Image Super-Resolution Self-Learning +1

Inheritance-guided Hierarchical Assignment for Clinical Automatic Diagnosis

no code implementations27 Jan 2021 Yichao Du, Pengfei Luo, Xudong Hong, Tong Xu, Zhe Zhang, Chao Ren, Yi Zheng, Enhong Chen

Clinical diagnosis, which aims to assign diagnosis codes for a patient based on the clinical note, plays an essential role in clinical decision-making.

Decision Making

Accurate and Fast reconstruction of Porous Media from Extremely Limited Information Using Conditional Generative Adversarial Network

no code implementations4 Apr 2019 Junxi Feng, Xiaohai He, Qizhi Teng, Chao Ren, Honggang Chen, Yang Li

To overcome this shortcoming, in this study we proposed a deep learning-based framework for reconstructing full image from its much smaller sub-area(s).

Image Reconstruction

CISRDCNN: Super-resolution of compressed images using deep convolutional neural networks

no code implementations19 Sep 2017 Honggang Chen, Xiaohai He, Chao Ren, Linbo Qing, Qizhi Teng

Experiments on compressed images produced by JPEG (we take the JPEG as an example in this paper) demonstrate that the proposed CISRDCNN yields state-of-the-art SR performance on commonly used test images and imagesets.

Image Super-Resolution

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