Search Results for author: Xiao-Ping Zhang

Found 34 papers, 2 papers with code

SAFARI: Sparsity enabled Federated Learning with Limited and Unreliable Communications

no code implementations5 Apr 2022 Yuzhu Mao, Zihao Zhao, Meilin Yang, Le Liang, Yang Liu, Wenbo Ding, Tian Lan, Xiao-Ping Zhang

It is demonstrated that SAFARI under unreliable communications is guaranteed to converge at the same rate as the standard FedAvg with perfect communications.

Federated Learning Sparse Learning

Refine-Net: Normal Refinement Neural Network for Noisy Point Clouds

1 code implementation23 Mar 2022 Haoran Zhou, Honghua Chen, Yingkui Zhang, Mingqiang Wei, Haoran Xie, Jun Wang, Tong Lu, Jing Qin, Xiao-Ping Zhang

Differently, our network is designed to refine the initial normal of each point by extracting additional information from multiple feature representations.

Parameterized Image Quality Score Distribution Prediction

no code implementations2 Mar 2022 Yixuan Gao, Xiongkuo Min, Wenhan Zhu, Xiao-Ping Zhang, Guangtao Zhai

Experimental results verifythe feasibility of using alpha stable model to describe the IQSD, and prove the effectiveness of objective alpha stable model basedIQSD prediction method.

Sequential Doppler Shift based Optimal Localization and Synchronization with TOA

no code implementations14 Feb 2022 Sihao Zhao, Ningyan Guo, Xiao-Ping Zhang, Xiaowei Cui, Mingquan Lu

In this paper, we develop a new optimal LAS method in the TDBS, namely LAS-SDT, by taking advantage of the sequential Doppler shift and TOA measurements.

Closed-form Two-way TOA Localization and Synchronization for User Devices with Motion and Clock Drift

no code implementations13 Nov 2021 Sihao Zhao, Ningyan Guo, Xiao-Ping Zhang, Xiaowei Cui, Mingquan Lu

Numerical results in a 3D scenario verify the theoretical analysis that the estimation accuracy of the new CFTWLAS method reaches CRLB in the presented experiments when the number of the ANs is large, the geometry is appropriate, and the noise is small.

Time-Distributed Feature Learning in Network Traffic Classification for Internet of Things

no code implementations29 Sep 2021 Yoga Suhas Kuruba Manjunath, Sihao Zhao, Xiao-Ping Zhang

The network traffic classification (NTC) is an essential tool to explore behaviours of network flows, and NTC is required for Internet service providers (ISPs) to manage the performance of the IoT network.

Traffic Classification

Virtual Reality Gaming on the Cloud: A Reality Check

no code implementations21 Sep 2021 Sihao Zhao, Hatem Abou-zeid, Ramy Atawia, Yoga Suhas Kuruba Manjunath, Akram Bin Sediq, Xiao-Ping Zhang

To the best of the authors' knowledge, this is the first measurement study and analysis conducted using a commercial cloud VR gaming platform, and under both fixed and adaptive bitrate streaming.


Direction-aware Feature-level Frequency Decomposition for Single Image Deraining

no code implementations15 Jun 2021 Sen Deng, Yidan Feng, Mingqiang Wei, Haoran Xie, Yiping Chen, Jonathan Li, Xiao-Ping Zhang, Jing Qin

Second, we further establish communication channels between low-frequency maps and high-frequency maps to interactively capture structures from high-frequency maps and add them back to low-frequency maps and, simultaneously, extract details from low-frequency maps and send them back to high-frequency maps, thereby removing rain streaks while preserving more delicate features in the input image.

Single Image Deraining

Exploiting Relationship for Complex-scene Image Generation

no code implementations1 Apr 2021 Tianyu Hua, Hongdong Zheng, Yalong Bai, Wei zhang, Xiao-Ping Zhang, Tao Mei

Our method tends to synthesize plausible layouts and objects, respecting the interplay of multiple objects in an image.

Image Generation Scene Generation

A New TOA Localization and Synchronization System with Virtually Synchronized Periodic Asymmetric Ranging Network

no code implementations17 Mar 2021 Sihao Zhao, Xiao-Ping Zhang, Xiaowei Cui, Mingquan Lu

In this article, we design a new time-of-arrival (TOA) system for simultaneous user device (UD) localization and synchronization with a periodic asymmetric ranging network, namely PARN.

Non-local Channel Aggregation Network for Single Image Rain Removal

no code implementations3 Mar 2021 Zhipeng Su, Yixiong Zhang, Xiao-Ping Zhang, Feng Qi

Second, aggregating channels could help our model to concentrate on channels more related to image background instead of rain streaks.

Rain Removal

Semidefinite Programming Two-way TOA Localization for User Devices with Motion and Clock Drift

no code implementations3 Mar 2021 Sihao Zhao, Xiao-Ping Zhang, Xiaowei Cui, Mingquan Lu

In two-way time-of-arrival (TOA) systems, a user device (UD) obtains its position by round-trip communications to a number of anchor nodes (ANs) at known locations.

New Closed-form Joint Localization and Synchronization using Sequential One-way TOAs

no code implementations30 Jan 2021 Ningyan Guo, Sihao Zhao, Xiao-Ping Zhang, Zheng Yao, Xiaowei Cui, Mingquan Lu

Compared with the conventional iterative method, the proposed new CFJLAS method does not require initialization, obtains the optimal solution under the small noise condition, and has a low computational complexity.

A Closed-form Localization Method Utilizing Pseudorange Measurements from Two Non-synchronized Positioning Systems

no code implementations25 Nov 2020 Sihao Zhao, Xiao-Ping Zhang, Xiaowei Cui, Mingquan Lu

Numerical results verify the theoretical analysis on positioning accuracy, and show that the new CDL method has superior performance over the state-of-the-art closed-form method.

Optimal Two-way TOA Localization and Synchronization for Moving User Devices with Clock Drift

no code implementations24 Nov 2020 Sihao Zhao, Xiao-Ping Zhang, Xiaowei Cui, Mingquan Lu

We show that the conventional two-way TOA method is a special case of the TWLAS when the UD is stationary, and the TWLAS has high estimation accuracy than the conventional one-way TOA method.

Identification of deep breath while moving forward based on multiple body regions and graph signal analysis

no code implementations20 Oct 2020 Yunlu Wang, Cheng Yang, Menghan Hu, Jian Zhang, Qingli Li, Guangtao Zhai, Xiao-Ping Zhang

This paper presents an unobtrusive solution that can automatically identify deep breath when a person is walking past the global depth camera.

Claw U-Net: A Unet-based Network with Deep Feature Concatenation for Scleral Blood Vessel Segmentation

no code implementations20 Oct 2020 Chang Yao, Jingyu Tang, Menghan Hu, Yue Wu, Wenyi Guo, Qingli Li, Xiao-Ping Zhang

Sturge-Weber syndrome (SWS) is a vascular malformation disease, and it may cause blindness if the patient's condition is severe.

Change Detection in Heterogeneous Optical and SAR Remote Sensing Images via Deep Homogeneous Feature Fusion

no code implementations8 Apr 2020 Xiao Jiang, Gang Li, Yu Liu, Xiao-Ping Zhang, You He

To solve this problem, this paper presents a new homogeneous transformation model termed deep homogeneous feature fusion (DHFF) based on image style transfer (IST).

Change Detection Style Transfer

Dynamic Spatiotemporal Graph Neural Network with Tensor Network

no code implementations12 Mar 2020 Chengcheng Jia, Bo Wu, Xiao-Ping Zhang

Dynamic spatial graph construction is a challenge in graph neural network (GNN) for time series data problems.

graph construction Time Series

Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner

no code implementations12 Feb 2020 Yunlu Wang, Menghan Hu, Qingli Li, Xiao-Ping Zhang, Guangtao Zhai, Nan Yao

During the epidemic prevention and control period, our study can be helpful in prognosis, diagnosis and screening for the patients infected with COVID-19 (the novel coronavirus) based on breathing characteristics.

Point cloud denoising based on tensor Tucker decomposition

no code implementations20 Feb 2019 Jianze Li, Xiao-Ping Zhang, Tuan Tran

In this paper, we propose a new algorithm for point cloud denoising based on the tensor Tucker decomposition.


Interactive Binary Image Segmentation with Edge Preservation

no code implementations10 Sep 2018 Jianfeng Zhang, Liezhuo Zhang, Yuankai Teng, Xiao-Ping Zhang, Song Wang, Lili Ju

Binary image segmentation plays an important role in computer vision and has been widely used in many applications such as image and video editing, object extraction, and photo composition.

Interactive Segmentation Semantic Segmentation +1

Multimodal Fusion via a Series of Transfers for Noise Removal

no code implementations22 Jan 2017 Chang-Hwan Son, Xiao-Ping Zhang

Different from conventional fusion approaches, the proposed method conducts a series of transfers: contrast, detail, and color transfers.

Rain Removal via Shrinkage-Based Sparse Coding and Learned Rain Dictionary

no code implementations3 Oct 2016 Chang-Hwan Son, Xiao-Ping Zhang

Based on this error map, both the sparse codes of rain and non-rain dictionaries are used jointly to represent the image structures of objects and avoid the edge artifacts in the non-rain regions.

Dictionary Learning Image Restoration +1

Rain structure transfer using an exemplar rain image for synthetic rain image generation

no code implementations3 Oct 2016 Chang-Hwan Son, Xiao-Ping Zhang

Next, residual rain patches are selected randomly, and then added to the given target image along a raster scanning direction.

Image Generation Rain Removal

Near-Infrared Coloring via a Contrast-Preserving Mapping Model

no code implementations3 Oct 2016 Chang-Hwan Son, Xiao-Ping Zhang

This paper introduces a new coloring method to add colors to near-infrared gray images based on a contrast-preserving mapping model.

Denoising Image Restoration

Near-Infrared Image Dehazing Via Color Regularization

no code implementations1 Oct 2016 Chang-Hwan Son, Xiao-Ping Zhang

It is also shown that the proposed color regularization can remove the edge artifacts which arise from the use of the conventional dark prior model.

Image Dehazing

Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI

no code implementations12 Feb 2013 Yue Huang, John Paisley, Qin Lin, Xinghao Ding, Xueyang Fu, Xiao-Ping Zhang

The size of the dictionary and the patch-specific sparsity pattern are inferred from the data, in addition to other dictionary learning variables.

Denoising Dictionary Learning +2

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