no code implementations • 29 Apr 2024 • Wenbin Guan, Zijiu Yang, Xiaohong Wu, Liqiong Chen, Feng Huang, Xiaohai He, Honggang Chen
Presently, the task of few-shot object detection (FSOD) in remote sensing images (RSIs) has become a focal point of attention.
no code implementations • 10 Aug 2023 • Yanteng Zhang, Qizhi Teng, Xiaohai He, Tong Niu, Lipei Zhang, Yan Liu, Chao Ren
Structural MRI and PET imaging play an important role in the diagnosis of Alzheimer's disease (AD), showing the morphological changes and glucose metabolism changes in the brain respectively.
no code implementations • 31 Jul 2023 • Yanteng Zhanga, Xiaohai He, Yi Hao Chan, Qizhi Teng, Jagath C. Rajapakse
In this study, we demonstrate how brain networks can be created from sMRI or PET images and be used in a population graph framework that can combine phenotypic information with imaging features of these brain networks.
1 code implementation • 25 Apr 2023 • Zhenchuan Ma, Xiaohai He, Pengcheng Yan, Fan Zhang, Qizhi Teng
The proposed algorithm is flexible and can complete training and reconstruction in a short time with only one two-dimensional image.
no code implementations • 16 May 2022 • Pengcheng Yan, Qizhi Teng, Xiaohai He, Zhenchuan Ma, Ningning Zhang
Digital modeling of the microstructure is important for studying the physical and transport properties of porous media.
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.
1 code implementation • 3 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.
no code implementations • 11 Apr 2019 • Xiang Chen, Lingbo Qing, Xiaohai He, Xiaodong Luo, Yining Xu
With a novel fully-trained generative network, FTGAN can synthesize higher-quality images and urge the outputs of the FTGAN are more relevant to the input sentences.
no code implementations • 4 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).
no code implementations • 24 Jun 2018 • Yu-Kai Wang, Qizhi Teng, Xiaohai He, Junxi Feng, Tingrong Zhang
Super resolution (SR) methods based on deep learning have achieved surprising performance in two-dimensional (2D) images.
no code implementations • 27 May 2018 • Honggang Chen, Xiaohai He, Linbo Qing, Shuhua Xiong, Truong Q. Nguyen
The pixel domain deep network takes the four downsampled versions of the compressed image to form a 4-channel input and outputs a pixel domain prediction, while the wavelet domain deep network uses the 1-level discrete wavelet transformation (DWT) coefficients to form a 4-channel input to produce a DWT domain prediction.
Ranked #7 on JPEG Artifact Correction on LIVE1 (Quality 20 Color)
no code implementations • 19 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.
no code implementations • 30 Jun 2015 • Yuanyuan Wu, Xiaohai He, Byeongkeun Kang, Haiying Song, Truong Q. Nguyen
This letter presents a novel approach to extract reliable dense and long-range motion trajectories of articulated human in a video sequence.