Search results for: Shixiong Xia

Items from 1 to 20 out of 30 results

article

An overview on trajectory outlier detection

Fanrong Meng, Guan Yuan, Shaoqian Lv, Zhixiao Wang, more

Artificial Intelligence Review > 2019 > 52 > 4 > 2437-2456

The task of trajectory outlier detection is to discover trajectories or their segments which differ substantially from or are inconsistent with the remaining set. In this paper, we make an overview on trajectory outlier detection algorithms from three aspects. Firstly, algorithms considering multi-attribute. In this kind of algorithms, as many key attributes as possible, such as speed, direction,...

article

Constructions of involutions with optimal minimum degree

Fengrong Zhang, Shixiong Xia, Yupu Hu, Min Xie

IET Information Security > 2017 > 11 > 5 > 261 - 266

The minimum degree (resp. algebraic degree) of a Boolean permutation is the minimum (resp. maximum) algebraic degree of all the non-zero linear combinations of its coordinate functions. In this study, the authors concentrate on the design of Boolean permutations with optimal minimum degree. First, they present a novel method for optimising the minimum degrees of known Boolean permutations. Second,...

article

Real-Time Correlation Filter Tracking by Efficient Dense Belief Propagation With Structure Preserving

Rui Yao, Shixiong Xia, Zhen Zhang, Yanning Zhang

IEEE Transactions on Multimedia > 2017 > 19 > 4 > 772 - 784

Patch-based models that combine local image features or regions into loose geometric assemblies are a powerful paradigm for visual object tracking, and they present favorable properties such as robustness to partial occlusion, deformation, and the ability to address viewpoint changes. However, effectively exploiting the spatial-temporal confidence scores of each patch to construct a robust tracker...

article

Robust lifelong visual tracking using compact binary feature with color attributes

Rui Yao, Shixiong Xia, Yong Zhou, Qiang Niu

Neurocomputing > 2016 > 213 > C > 172-182

In this paper, we address the problem of visual tracking where the target object undergo appearance variations due to illumination variation, occlusion, motion, background clutter and deformation. To deal with the significant appearance variations, we introduce color attributes into traditional shape feature at cell level, the new feature representation takes into consideration both its photometric...

article

Exploiting Spatial Structure from Parts for Adaptive Kernelized Correlation Filter Tracker

Rui Yao, Shixiong Xia, Fumin Shen, Yong Zhou, more

IEEE Signal Processing Letters > 2016 > 23 > 5 > 658 - 662

Decomposing target into several parts may improve the capability of tracking algorithm to deal with appearance variations such as occlusion and deformation. In this letter, we propose a part-based appearance model by exploiting spatial structure from parts. The model minimizes appearance and deformation cost simultaneously to predict the new position of object. Then, the optimization problem is divided...

chapter

Multi-relational Data Semi-supervised K-Means Clustering Algorithm

Zhanguo Xia, Wentao Zhang, Shiyu Cai, Shixiong Xia

Lecture Notes in Computer Science > Artificial Intelligence and Computational Intelligence > Data Mining and Knowledge Discovering > 413-420

Based on the traditional K-means clustering algorithm, a new semi-supervised K-means clustering algorithm (MMK-means) is proposed in this paper, in which use semi-supervised learning method to solve the problem of clustering on multi-relational data set. In order to improve the quality of clustering results, the algorithm making full use of the various relationships between objects and attributes...

chapter

Supervised Information Feature Compression Algorithm Based on Divergence Criterion

Shiei Ding, Wei Ning, Fengxiang Jin, Shixiong Xia, more

Lecture Notes in Computer Science > Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence > Fine Feature Extraction Methods > 919-925

In this paper, a novel supervised information feature compression algorithm based on divergence criterion is set up. Firstly, according to the information theory, the concept and its properties of the discrete divergence, i.e. average separability information (ASI) is studied, and a concept of symmetry average separability information (SASI) is proposed, and proved that the SASI here is a kind of...

article

Further results on constructions of generalized bent Boolean functions

Fengrong Zhang, Shixiong Xia, Pantelimon Stănică, Yu Zhou

Science China Information Sciences > 2016 > 59 > 5 > 1-3

摘要创新点对文献 [Stanica P, Martinsen T, Gangopadhyay S, Singh B J. Bent and generalized bent Boolean functions. Des. Codes Cryptogr., 2013, 69: 77–94.]中的三个重要结果做了进一步的研究。第一, 通过对关于 2 个变元对称的 n+2 元广义 bent 函数的研究, 刻画了一类关于 m 个变元对称的 n+m 元广义 bent 函数, 其中 m 为偶数。第二, 基于广义 bent 函数已知抽象结果, 给出了构造该类广义 bent 函数几种具体的新方法, 提高了过去的结果。

article

Robust tracking via online Max-Margin structural learning with approximate sparse intersection kernel

Rui Yao, Shixiong Xia, Yong Zhou

Neurocomputing > 2015 > 157 > Complete > 344-355

In this paper, we propose a robust visual tracking algorithm using online Max-Margin structural learning with sparse intersection kernel approximations to address the appearance variation, such as pose and scale variations, illumination changes, and occlusion. In the proposed tracking framework, we introduce a new sparse approximate HOG-based appearance model to represent the tracked object in high-dimensional...

article

Semi-supervised extreme learning machine with manifold and pairwise constraints regularization

Yong Zhou, Beizuo Liu, Shixiong Xia, Bing Liu

Neurocomputing > 2015 > 149 > Part A > 180-186

Traditional kernel-based semi-supervised learning (SSL) algorithms usually have high computational complexity. Moreover, few SSL methods have been proposed to utilize both the manifold of unlabeled data and pairwise constraints effectively. In this paper, we first construct a unified SSL framework to combine the manifold regularization and the terms based on the pairwise constraints for semi-supervised...

chapter

Congestion Avoidance for Band-Typed Wireless Sensor Networks in Coalmine Tunnel

Gongbo Zhou, Peng Zhang, Zhencai Zhu, Shixiong Xia

2015 International Conference on Network and Information Systems for Computers > 55 - 58

2015 International Conference on Network and Information Systems for Computers (ICNISC)

Comparing to the regular wireless sensor networks, congestion occurs with higher probability in the band-typed wireless sensor networks as the limits of the geography character. In this paper, we take the band-typed wireless sensor networks with Zigbee protocol for gas monitoring in coalmine tunnel as example. The congestion situations of band-typed wireless sensor networks are discussed firstly....

article

Multiple small objects tracking based on dynamic Bayesian networks with spatial prior

Rui Yao, Yanning Zhang, Yong Zhou, Shixiong Xia, more

Optik - International Journal for Light and Electron Optics > 2014 > 125 > 10 > 2243-2247

This paper proposes an end-to-end algorithm for multiple small objects tracking in noisy video using a combination of Gaussian mixture based background segmentation along with a Dynamic Bayesian Networks (DBNs) based tracking. Background segmentation is based on an adaptive backgrounding method that models each pixel as a mixture of Gaussians with spatial prior and uses an online approximation to...

chapter

A Majorization-Minimization Approach to Lq Norm Multiple Kernel Learning

Zhizheng Liang, Shixiong Xia, Jin Liu, Yong Zhou, more

2013 2nd IAPR Asian Conference on Pattern Recognition > 366 - 370

2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR)

Multiple kernel learning (MKL) usually searches for linear (nonlinear) combinations of predefined kernels by optimizing some performance measures. However, previous MKL algorithms cannot deal with Lq norm MKL if q

article

Training Lp norm multiple kernel learning in the primal

Zhizheng Liang, Shixiong Xia, Yong Zhou, Lei Zhang

Neural Networks > 2013 > 46 > Complete > 172-182

Some multiple kernel learning (MKL) models are usually solved by utilizing the alternating optimization method where one alternately solves SVMs in the dual and updates kernel weights. Since the dual and primal optimization can achieve the same aim, it is valuable in exploring how to perform Lp norm MKL in the primal. In this paper, we propose an Lp norm multiple kernel learning algorithm in the primal...

article

Feature extraction based on Lp-norm generalized principal component analysis

Zhizheng Liang, Shixiong Xia, Yong Zhou, Lei Zhang, more

Pattern Recognition Letters > 2013 > 34 > 9 > 1037-1045

In this paper, we propose Lp-norm generalized principal component analysis (PCA) by maximizing a class of convex objective functions. The successive linearization technique is used to solve the proposed optimization model. It is interesting to note that the closed-form solution of the subproblem in the algorithm can be achieved at each iteration. Meanwhile, we theoretically prove the convergence of...

article

Normalized discriminant analysis for dimensionality reduction

Zhizheng Liang, Shixiong Xia, Yong Zhou

Neurocomputing > 2013 > 110 > Complete > 153-159

In this paper, we propose the normalized discriminant analysis (NDA) technique for dimensionality reduction. NDA is built on the information of data point pairs that is implicitly encoded by using the pseudo-Riemannian metric tensor. This makes NDA to be easily adapted for unsupervised or supervised learning. It is also interesting to note that the solution of NDA will asymptotically converge to that...

article

Adaptive weighted learning for linear regression problems via Kullback–Leibler divergence

Zhizheng Liang, Youfu Li, ShiXiong Xia

Pattern Recognition > 2013 > 46 > 4 > 1209-1219

In this paper, we propose adaptive weighted learning for linear regression problems via the Kullback–Leibler (KL) divergence. The alternative optimization method is used to solve the proposed model. Meanwhile, we theoretically demonstrate that the solution of the optimization algorithm converges to a stationary point of the model. In addition, we also fuse global linear regression and class-oriented...

article

Blockwise projection matrix versus blockwise data on undersampled problems: Analysis, comparison and applications

Zhizheng Liang, Shixiong Xia, Yong Zhou, Youfu Li

Pattern Recognition > 2011 > 44 > 10-11 > 2774-2785

Linear subspace methods are extensively used in many areas such as pattern recognition and machine learning. Among them, block subspace methods are efficient in terms of the computational complexity. In this paper, we perform a thorough analysis on block subspace methods and give a theoretical framework for understanding block subspace methods. It reveals the relationship between block subspace methods...

chapter

An anomaly detection approach based on symbolic similarity

Qiuyan Yan, Shixiong Xia, Yilong Shi

2010 Chinese Control and Decision Conference > 3003 - 3008

2010 Chinese Control and Decision Conference (CCDC)

Anomaly detection technology has two broad categories: segmentation based and kernel based anomaly detection techniques. According to different similarity measures,kernel based anomaly detection techniques including KNNC (k-nearest neighbor for continuous time series) and KNND (a discrete version of KNNC) method. KNNC has better accuracy but lower efficiency than KNND, but KNND would lost information...

chapter

A Method of Fuzzy Reasoning Based on Semantic Similarity and Bipartite Graph Matching

Qiang Niu, Shixiong Xia, Guojun Tan, Zuhui Hu

2009 International Conference on Artificial Intelligence and Computational Intelligence > 4 > 141 - 145

2009 International Conference on Artificial Intelligence and Computational Intelligence (AICI 2009)

For the shortcomings of fuzzy rule reasoning method in traditional fault diagnosis expert system, a fuzzy rule matching method based on semantic similarity and bipartite graph is proposed in this paper. Firstly, fault domain knowledge ontology is built by analyzing domain fault knowledge, and then the input fault phenomena set and the property set of rule set antecedent act as the vertex sets of bipartite...

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INFONA - science communication portal

Search results for: Shixiong Xia

An overview on trajectory outlier detection

Constructions of involutions with optimal minimum degree

Real-Time Correlation Filter Tracking by Efficient Dense Belief Propagation With Structure Preserving

Robust lifelong visual tracking using compact binary feature with color attributes

Exploiting Spatial Structure from Parts for Adaptive Kernelized Correlation Filter Tracker

Multi-relational Data Semi-supervised K-Means Clustering Algorithm

Supervised Information Feature Compression Algorithm Based on Divergence Criterion

Further results on constructions of generalized bent Boolean functions

Robust tracking via online Max-Margin structural learning with approximate sparse intersection kernel

Semi-supervised extreme learning machine with manifold and pairwise constraints regularization

Congestion Avoidance for Band-Typed Wireless Sensor Networks in Coalmine Tunnel

Multiple small objects tracking based on dynamic Bayesian networks with spatial prior

A Majorization-Minimization Approach to Lq Norm Multiple Kernel Learning

Training Lp norm multiple kernel learning in the primal

Feature extraction based on Lp-norm generalized principal component analysis

Normalized discriminant analysis for dimensionality reduction

Adaptive weighted learning for linear regression problems via Kullback–Leibler divergence

Blockwise projection matrix versus blockwise data on undersampled problems: Analysis, comparison and applications

An anomaly detection approach based on symbolic similarity

A Method of Fuzzy Reasoning Based on Semantic Similarity and Bipartite Graph Matching

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