A5004039264- Image and Signal Denoising Methods
- Advanced Image Processing Techniques
- Advanced Image Fusion Techniques
- Medical Image Segmentation Techniques
- Image Processing Techniques and Applications
- Stock Market Forecasting Methods
- Data Mining Algorithms and Applications
- AI in cancer detection
- Image Retrieval and Classification Techniques
- Sparse and Compressive Sensing Techniques
- Industrial Vision Systems and Defect Detection
- Big Data and Business Intelligence
- Radiomics and Machine Learning in Medical Imaging
- Image and Object Detection Techniques
- Advanced Neural Network Applications
- Advanced Computational Techniques and Applications
- Service-Oriented Architecture and Web Services
- Blind Source Separation Techniques
- Brain Tumor Detection and Classification
- Rough Sets and Fuzzy Logic
- Energy Load and Power Forecasting
- Metaheuristic Optimization Algorithms Research
- Energy Efficient Wireless Sensor Networks
- Wireless Signal Modulation Classification
- Data Quality and Management
Xinjiang Agricultural University
2025
Shandong University of Finance and Economics
2015-2024
Shandong University
2007-2024
Chinese Academy of Medical Sciences & Peking Union Medical College
2022-2024
Guilin University of Technology
2015-2024
Chongqing Jiaotong University
2024
China University of Petroleum, East China
2023
Anhui Business College
2023
State Key Laboratory of Vehicle NVH and Safety Technology
2023
Air Force Medical University
2020-2022
Nonlocal self-similarity of images has attracted considerable interest in the field image processing and led to several state-of-the-art denoising algorithms, such as block matching 3-D, principal component analysis with local pixel grouping, patch-based locally optimal wiener, spatially adaptive iterative singular-value thresholding. In this paper, we propose a computationally simple algorithm using nonlocal low-rank approximation (LRA). The proposed method consists three basic steps....
To recover the corrupted pixels, traditional inpainting methods based on low-rank priors generally need to solve a convex optimization problem by an iterative singular value shrinkage algorithm. In this paper, we propose simple method for image using low rank approximation, which avoids time-consuming shrinkage. Specifically, if similar patches of are identified and reshaped as vectors, then patch matrix can be constructed collecting these patch-vectors. Due its columns being highly linearly...
A deep convolutional neural network has recently witnessed rapid progress due to the strong feature learning capability. In this paper, we focus on its application in industrial field and propose a method based fully (FCN) for detecting defects tire X-ray images. Owing capability of pixel-wise prediction FCN, location, segmentation are completed simultaneously. The architecture used mainly consists three phases. first phase is traditional network, which extract images, maps obtained at last...
This study investigates the inclusion of spatio-temporal correlation and interaction in a multivariate random-parameters Tobit model their influence on fitting areal crash rates with different severity outcomes. The spatial is specified via conditional autoregressiv (MCAR) prior, whereas temporal by linear time trend. A formulated as product trend term an MCAR prior. developed for slight injury killed or serious using one year data from 131 traffic analysis zones Hong Kong. proposed...
Resembling the role of disease diagnosis in Western medicine, pathogenesis (also called Bing Ji) is one utmost important tasks traditional Chinese medicine (TCM). In TCM theory, a complex system composed group interrelated factors, which highly consistent with character systems science (SS). this paper, we introduce heuristic definition network (PN) to represent form directed graph. Accordingly, computational method diagnosis, differentiation (ND), proposed by integrating holism principle...
The object detection technology for Synthetic Aperture Radar (SAR) image generation is of great significance in signal processing, radar imaging and other fields. SAR the data obtained from electromagnetic wave echo to after processing range azimuth respectively. However, sizes objects be detected change dramatically difficulty increases, because scattering characteristics waves have a influence on images. At same time, large areas background information will contain confused geographical...
This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus proposed methods and results.In this challenge, new Large-scale Diverse Video (LDV) dataset is employed.The has three tracks.Tracks 1 2 aim at enhancing videos by HEVC fixed QP, while Track 3 designed for x265 bit-rate.Besides, Tracks targets improving fidelity (PSNR), perceptual quality.The tracks totally attract 482 registrations.In test phase, 12 teams, 8 teams 11 submitted final results...
Automatic defect detection is an important and challenging problem in industrial quality inspection. This paper proposes efficient method for tire assurance, which takes advantage of the feature similarity images to capture anomalies. The proposed algorithm mainly consists three steps. Firstly, local kernel regression descriptor exploited derive a set vectors inspected image. These are used evaluate dissimilarity pixels. Next, texture distortion degree each pixel estimated by weighted...
Today, one of the most important factors for success cloud computing is to create trust and security. Cloud will face a lot challenges when key element absent. There are no special evaluation models environment. In this paper, definition in systems introduced properties analyzed. Based on semantics trust, an extensible model named ETEC proposed, which includes time-variant comprehensive method expressing direct space-variant calculating recommendation trust. To compute systems, algorithm...
Stock price volatility forecasting is a hot topic in time series prediction research, which plays an important role reducing investment risk. However, the trend of stock not only depends on its historical trend, but also related social factors. This paper proposes hybrid time-series predictive neural network (HTPNN) that combines effection news. The features news headlines are expressed as distributed word vectors dimensionally reduced to optimize efficiency model by sparse automatic...
Abstract Background Several studies have proposed grading systems for risk stratification of early‐stage lung adenocarcinoma based on histological patterns. However, the reproducibility these is poor in clinical practice, indicating need to develop a new system which easy apply and has high accuracy prognostic patients. Methods Patients with stage I invasive nonmucinous were retrospectively collected from pathology archives between 2009 2016. The patients divided into training validation set...
Tensor robust principal component analysis (TRPCA) is a classical way for low-rank tensor recovery, which minimizes the convex surrogate of rank by shrinking each singular value equally. However, real-world visual data, large values represent more significant information than small values. In this paper, we propose nonconvex TRPCA (N-TRPCA) model based on adjustable logarithmic norm. Unlike TRPCA, our N-TRPCA can adaptively shrink and less. addition, assumes that whole data low rank. This...
Security of cloud computing is one the challenges to be addressed before novel pas-as-you-go business model widely applied, and dependability most important means improve security current heterogeneous platforms. Previous research on in systems only uses qualitative approaches there are few systematic works systems. In this paper, definition given a series quantitative indicators presented evaluate dependability. A CDSV established enhance environments. System-level virtualization techniques...
In this paper, we propose a new tire defect detection algorithm based on dictionary representation. The learned from normal images is efficient to represent defect-free while it has low efficiency due its capability of capturing key information. Unlike the conventional iterative solution with complicated calculation, representation coefficients are obtained by multiplying pseudo-inverse matrix and image patch. Moreover, distribution very different between image. Therefore, difference can be...