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| 1 | Robust sparse principal component analysis显示文摘The model for improving the robustness of sparse principal component analysis(PCA)is proposed in this paper.Instead of the l2-norm variance utilized in the conventional sparse PCA model,the proposed model maximizes the l1-norm variance,which is less sensitive to noise and outlier.To ensure sparsity,lp-norm(0 p 1)constraint,which is more general and effective than l1-norm,is considered.A simple yet efficient algorithm is developed against the proposed model.The complexity of the algorithm approximately linearly increases with both of the size and the dimensionality of the given data,which is comparable to or better than the current sparse PCA methods.The proposed algorithm is also proved to converge to a reasonable local optimum of the model.The efficiency and robustness of the algorithm is verified by a series of experiments on both synthetic and digit number image data. | ZHAO Qian MENG DeYu XU ZongBen | 2014 | Science China(Information Sciences)2014，57，9： | 5 |
| 2 | Some New Trends of Deep Learning Research显示文摘Deep learning has been attracting increasing attention in the recent decade throughout science and engineering due to its wide range of successful applications.In real problems,however,most implementation stages for applying deep learning still require inevitable manual interventions,which naturally conducts difficulty in its availability to general users with less expertise and also deviates from the intelligence of humans.It is thus a challenging while critical issue to enhance the level of automation across all elements of the entire deep learning framework,like input amelioration,model designing and learning,and output adjustment.This paper tries to list several representative issues of this research topic,and briefly describe their recent research progress and some related works proposed along this research line.Some specific challenging problems have also been presented. | MENG Deyu SUN Lina | 2019 | Chinese Journal of Electronics2019，28，6： | 3 |
| 3 | In-situ Synthesis and Characterization of Poly(vinyl alcohol)/Hydroxyapatite Composite Hydrogel by Freezing-thawing Method显示文摘Poly(vinyl alcohol)/hydroxyapatite(PVA/HA) composite hydrogel was successfully in-situ synthesized via three cycles of freezing-thawing. The composition and structure of products were investigated by X-ray diffraction( XRD), Fourier transformed infrared spectroscopy(FTIR) and scanning electron microscopy(SEM). The influence of different preparation methods and contents of material on the mechanical properties of PVA/HA composite hydrogel was discussed through tensile and compressive tests. The template of PVA could avoid the agglomeration of HA particles, which improves the mechanical properties of the composite hydrogel effectively. The tensile strength, modulus and compressive performances of the PVA/HA composite hydrogel prepared by the in-situ synthesis method were better than those of hydrogel obtained by the simple blend metliod. In addition, the effect of the content of PVA, HA, and the pH value on tlie properties of tlie PVA/HA composite hydrogel has been discussed in detail. | MENG Deyue ZHOU Xiuqing ZHENG Keyan MIAO Chong SHENG Ye ZOU Haifeng | 2019 | Chemical Research in Chinese Universities2019，35，3： | 3 |
| 4 | Sparse recovery: from vectors to tensors显示文摘Recent advances in various fields such as telecommunications, biomedicine and economics, among others, have created enormous amount of data that are often characterized by their huge size and high dimensionality. It has become evident, from research in the past couple of decades, that sparsity is a flexible and powerful notion when dealing with these data, both from empirical and theoretical viewpoints. In this survey, we review some of the most popular techniques to exploit sparsity, for analyzing high-dimensional vectors, matrices and higher-order tensors. | Yao Wang Deyu Meng Ming Yuan | 2018 | National Science Review2018，5，5： | 2 |
| 5 | Improving geo-desic distance estimation based on locally linear assumption 显示文摘 | Meng Deyu Yee Leung Xu Zongben | 2008 | Pattern Recognition Letters2008，29，7： | 1 |
| 6 | Infrared patch-image model for small target detection in a single image显示文摘 | GAO Chengqiang MENG Deyu YANG Yi | 2013 | IEEE Transactions on Image Processing2013，22，12： | 1 |
| 7 | Improve robustness of sparse PCA by L 1 -norm maximization显示文摘 | Deyu Meng Qian Zhao Zongben Xu | 2011 | Pattern Recognition2011，，1： | 1 |
| 8 | G-CSF/SCF exert beneficial effects via anti-apoptosis in rabbits with steroid-associated osteonecrosis显示文摘 | Xinghuo Wu Shuhua Yang Hong Wang Chunqing Meng Weihua Xu Deyu Duan Xianzhe Liu | 2013 | Experimental and Molecular Pathology2013，，1： | 1 |
| 9 | Passage method for nonlinear dimensionality reduction of data on multi-cluster manifolds 显示文摘 | Meng Deyu Leung Y Xu Zongben | 2013 | Pattern Recognition2013，46，8： | 1 |
| 10 | Improve robustness of sparse PCA by Ll-norm maximization 显示文摘 | Meng Deyu Zhao Qian Xu Zongben | 2012 | Pattern Recogni- tion2012，45，1： | 1 |
| 11 | A more efficient preprocessing method for support vector classification显示文摘 | Meng Deyu Xu Zongben Jing Wenfeng | 2005 | IEEE/ICCN&B2005，2，1： | 1 |
| 12 | Improve robustness of sparse PCA by L 1 -norm maximization显示文摘 | Deyu Meng Qian Zhao Zongben Xu | 2011 | Pattern Recognition2011，，1： | 1 |
| 13 | Color and direction-invariant nonlocal self-similarity prior and its application to color image denoising显示文摘Nonlocal self-similarity(NSS)is one of the most commonly used priors in computer vision and image processing.It aims to make use of the fact that a natural image often possesses many repetitive local patterns,and thus a local image patch always has many similar patches across the image.Through compensatively integrating these similar image patches,their insightful patterns hiding under corrupted noises can be intrinsically extracted.However,for using this prior knowledge,current methods search the similar patches by using simple block matching strategy with Euclidean distance,which largely ignores those patches containing similar local patterns but with different texture-directions and colors.To more sufficiently explore similar patches over an image,in this paper,we propose two new representations for image patches,which facilitate an easy NSS prior for measuring direction-invariant and color-invariant nonlocal selfsimilarity possessed by image patches.Specifically,based on this prior term,we formulate the color image denoising problem as a concise Bayesian posterior estimation framework,and design an efficient expectationmaximization(EM)algorithm to solve it.A series of experiments implemented on simulated and real noisy color images demonstrate the superiority of the proposed method as compared with the state-of-the-arts both visually and quantitatively,verifying the potential usefulness of this new NSS prior. | Qi XIE Qian ZHAO Zongben XU Deyu MENG | 2020 | Science China(Information Sciences)2020，63，12： | 1 |
| 14 | A fast heuristic strategy for model selection of support vector machines显示文摘 | XU Zongben DAI Mingwei MENG Deyu | 2009 | IEEE Transactions on Systems Man and Cybernetics:part B2009，39，5： | 1 |
| 15 | A new quality assessment criterion for nonlinear dimensionality reduction显示文摘 | Deyu Meng Yee Leung Zongben Xu | 2011 | Neurocomputing2011，74，： | 1 |
| 16 | High performance 0.9LiMnPO4-0.1LiFePO4/C composite显示文摘The rate performance of lithium manganese phosphate is seriously tarnished by its sluggish surface kinetics,which could be addressed by LiFePO4-surface coating.For a higher energy output,here we explore thinner coating layers with 10%and 5%LiFePO4 via the lab-developed DMSO assisted method.The core-shell structured 0.9LiMnPO4-0.1LiFePO4/C maintains a high specific capacity,153,148 and 140 mA hg-1 under 0.1,1 and 5 C respectively,which are the best results for this composition till date.As for 0.95Li MnPO4-0.05 LiFePO4/C,the discharge capacity is lower than 110 mA hg-1 even in 0.1 C,which cannot meet the requirements of practical application.Our approaches push the manganese ratio of LiMnPO4-based composite to 90%from 80%,further improving the energy-density of the olivine phosphates. | LIU Jian ZHANG XianHui YANG WenChao LIU Meng REN ZhongMin ZHANG ShengQi WANG DeYu | 2020 | Science China(Technological Sciences)2020，63，6： | 1 |
| 17 | Structural limiting factors of mixed-valent tin oxides in photoelectrochemical application:A comparative exploration显示文摘Photoelectrocatalytic(PEC)materials for harvesting solar energy can be discovered from existing photocatalytic semiconductors.Nonetheless,mixed valence tin oxides,a group of widely reported visible light active photocatalysts,can hardly be developed into efficient PEC photoelectrodes.To overcome this difficulty by clarifying its origin,two typical mixed valence tin oxides,Sn^(2+):SnO_(2) microrods and porous Sn_(3)O_(4) particles were deliberately prepared as the models.Sn^(2+):SnO_(2) microrods of less porosity exhibited a photocurrent over ten times higher than Sn_(3)O_(4) particles.Photo-electrochemical impedance spectroscopy revealed this was due to their charge kinetics difference,specifically the internal transport/-transfer responding to the morphology.Moreover,hydroxyl residuals from synthesis were found to be very inhibitive for the PEC efficiency as well,which was in coherence with our TGA and Raman spectroscopic study.These finding experimentally proved the necessity of reconsidering the surface area,crystallinity,and defects when developing photocatalysts into efficient PEC structures. | Yalong Zou Deyu Liu Xiangrui Meng Qitao Liu Yang Zhou Jianming Li Zhiying Zhao Ding Chen Yongbo Kuang | 2021 | Journal of Energy Chemistry2021，30，5： | 0 |
| 18 | Survey on rain removal from videos or a single image显示文摘Rain can cause performance degradation of outdoor computer vision tasks.Thus,the exploration of rain removal from videos or a single image has drawn considerable attention in the field of image processing.Recently,various deraining methodologies have been proposed.However,no comprehensive survey work has yet been conducted to summarize existing deraining algorithms and quantitatively compare their generalization ability,and especially,no off-the-shelf toolkit exists for accumulating and categorizing recent representative methods for easy performance reproduction and deraining capability evaluation.In this regard,herein,we present a comprehensive overview of existing video and single image deraining methods as well as reproduce and evaluate current state-of-the-art deraining methods.In particular,these approaches are mainly classified into model-and deep-learning-based methods,and more elaborate branches of each method are presented.Inherent abilities,especially generalization performance,of the state-of-the-art methods have been both quantitatively and visually analyzed through thorough experiments conducted on synthetic and real benchmark datasets.Moreover,to facilitate the reproduction of existing deraining methods for general users,we present a comprehensive repository with detailed classification,including direct links to 85 deraining papers,24 relevant project pages,source codes of 12 and 25 algorithms for video and single image deraining,respectively,5 and 10 real and synthesized datasets,respectively,and 7 frequently used image quality evaluation metrics,along with the corresponding computation codes.Research limitations worthy of further exploration have also been discussed for future research along this direction. | Hong WANG Yichen WU Minghan LI Qian ZHAO Deyu MENG | 2022 | Science China(Information Sciences)2022，65，1： | 0 |
| 19 | Robust channel estimation based on the maximum entropy principle显示文摘Channel estimation(CE)is one of the crucial and fundamental elements of signal processing,especially considering the requirement of high accuracy in future wireless communication systems.Most traditional CE algorithms are explored under the assumption of Gaussian white noise,which limits the algorithms performance in real wireless communication situations.In this work,a novel self-adaptive CE algorithm based on the maximum entropy principle(MEP)was studied,which analyzes the statistical components of an arbitrary noise environment.In addition,an MEP channel-based signal estimation algorithm was studied.Furthermore,the statistical characteristics of channels were considered the regularization terms in the objective function for providing prior information and further increasing the accuracy.It was found that the proposed algorithm not only provides accurate CE but also reduces pilot consumption by using estimated signal data as pseudo pilots.The superior features of the proposed method concerning CE accuracy,pilot consumption,and robustness were confirmed through Monte Carlo simulations. | Zhengyang HU Jiang XUE Feng LI Qian ZHAO Deyu MENG Zongben XU | 2023 | Science China(Information Sciences)2023，66，12： | 0 |
| 20 | Robust low-rank tensor factorization by cyclic weighted median显示文摘Low-rank tensor factorization(LRTF) provides a useful mathematical tool to reveal and analyze multi-factor structures underlying data in a wide range of practical applications. One challenging issue in LRTF is how to recover a low-rank higher-order representation of the given high dimensional data in the presence of outliers and missing entries, i.e., the so-called robust LRTF problem. The L1-norm LRTF is a popular strategy for robust LRTF due to its intrinsic robustness to heavy-tailed noises and outliers. However, few L1-norm LRTF algorithms have been developed due to its non-convexity and non-smoothness, as well as the high order structure of data. In this paper we propose a novel cyclic weighted median(CWM) method to solve the L1-norm LRTF problem. The main idea is to recursively optimize each coordinate involved in the L1-norm LRTF problem with all the others fixed. Each of these single-scalar-parameter sub-problems is convex and can be easily solved by weighted median filter, and thus an effective algorithm can be readily constructed to tackle the original complex problem. Our extensive experiments on synthetic data and real face data demonstrate that the proposed method performs more robust than previous methods in the presence of outliers and/or missing entries. | MENG DeYu ZHANG Biao XU ZongBen ZHANG Lei GAO ChenQiang | 2015 | Science China(Information Sciences)2015，58，5： | 0 |
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