检索结果-内蒙古大学图书馆

International Joint Conference on Neural Networks

作者： Ying Wen Shicheng Yang Lili Hou Hongda Zhang Shanghai Key Laboratory of Multidimensional Information Processing Department of Computer Science and Technology East China Normal University

ISBN: (纸本)9781509006212

In this paper, we present a new and effective dimensionality reduction method called locality sparsity preserving projections (LSPP). Locality preserving projections (LPP) and sparsity preserving projections (SPP) only focus on an aspect of local structure and sparse reconstructive information of the dataset, respectively. The proposed method integrates the sparse reconstructive information and local structure of data. The projection of LSPP is sought such that the sparse reconstructive weights and local preserving weights can be best preserved and integrated. Extensive experiments on ORL, Yale, Yale B, AR and CMU PIE face databases show the effectiveness of the proposed LSPP.

关键词： Facial Recognition PROJECTION aspect Laryngology REDUCTION METHODS monuron project independence evaluation system

来源：评论

学校读者我要写书评

暂无评论

引用

23rd International Conference on Pattern Recognition, ICPR 2016

作者： Wang, Jin Zhu, Junkang Wang, Zheng Gao, Changxin Sang, Nong Rui, Huang National Key Laboratory of Science and Technology on Multispectral Information Processing School of Automation Huazhong University of Science and Technology China School of Physics Nanjing University China School of Computer Wuhan University China School of Science and Engineering Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781509048472

Person re-identification, aiming to match a specific person among non-overlapping cameras, has attracted plenty of attention in recent years. It can be regarded as a visual retrieval task, namely given a query person image, ranking all gallery images according to their similarities to the query. Conventionally, this similarity function is learnt by forcing intra-distances to be small while inter-distances to be large, which are referred to as individual similarity constraints. In this paper, we propose to learn the similarity function by taking into account of both individual similarity constraints and contextual similarity constraints. The context of a query is defined as its k-nearest neighbors in the gallery. We argue that if two images are from the same person, apart from the visual likeness between them, denoted as the individual similarity, they should also possess similar k-nearest neighbors in the gallery, denoted as the contextual similarity. Motivated by this assumption, we propose a new Contextual Similarity Regularized Metric Learning (CSRML) method for person re-identification. The contextual similarity regularization term forces two images of the same person to share similar context. Both individual and contextual similarity constraints are encoded by a large margin logistic loss function and the final problem is solved by the stochastic gradient descent algorithm. Experiments on the challenging VIPeR and CUHK01 datasets show that our approach achieves very competitive performance. © 2016 IEEE.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

The application based on Fourier transform in time lens

The application based on Fourier transform in time lens

引用

2016应用物理、光电子学和光学国际研讨会（APOP 2016）

作者： Rulin Liu Shuqin Guo Dacai Xu Zhejiang Provincial Key Laboratory for Signal Processing College of Information EngineeringZhejiang University of Technology Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai University

ISBN: (纸本)9781510825994

Using the similarity between the transmission of narrow band light pulses in the dispersion media and the transmission of spatial beam in paraxial diffraction,build a time lens system similar to the space *** lens can achieve compression and amplification of imaging function,and it has the nature of Fourier transform in light *** the time lens can also realize the compression and amplification of the light pulse and its Fourier *** the function of Fourier transform in the time domain of time lens system,achieved the effect of eliminating noise and removing side lobe,improved the white noise which generally exist in the communication system and the side lobe effect which will produce in the relevant processes.

关键词： domain The application based on Fourier transform in time lens Fourier

来源：评论

学校读者我要写书评

暂无评论

Neighborhood collaborative classifiers

Neighborhood collaborative classifiers

引用

2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016

作者： Xu, Suping Yang, Xibei Tsang, Eric C. C. Mantey, Eric A. School of Computer Science and Engineering Jiangsu University of Science and Technology Zhenjiang212003 China School of Economics and Management Nanjing University of Science and Technology Nanjing210094 China Faculty of Information Technology Macau University of Science and Technology C-Macau519020 China Intelligent Information Processing Key Laboratory of Shanxi Province Shanxi University Taiyuan030006 China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhejiang Ocean University Zhoushan316022 China

ISBN: (纸本)9781509003891

In neighborhood rough set model, the majority rule based neighborhood classifier (NC) is easy to be misjudged with the increasing of the size of information granules. To remedy this deficiency, we propose a neighborhood collaborative classifier (NCC) based on the idea of collaborative representation based classification (CRC). NCC first performs feature selection with neighborhood rough set, and then instead of solving the classification problem by the majority rule, NCC solves a similar problem with collaborative representation among the neighbors of each unseen sample. Experiments on UCI data sets demonstrate that: 1) Our NCC achieves satisfactory performance in larger neighborhood information granules when compared with NC;2) NCC reduces the size of dictionary when compared with CRC. © 2016 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Highly imbalanced classification using improved rotation forests

引用

International Journal of Wireless and Mobile Computing 2016年第1期10卷 35-41页

作者： Fang, Xiaonan Zheng, Xiyuan Tan, Yanyan Zhang, Huaxiang Department of Information Science and Engineering Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Shandong Normal University Jinan China

Imbalanced data classification is a challenging problem in data mining. It happens in many real-world applications and has attracted growing attentions from researchers. This issue occurs when the number of one class is much higher than the other class. Ensemble of classifiers has been well known as an effective solution. Then, two novel ensemble algorithms (RUROForest and SROForest) based on rotation forests are proposed for solving highly imbalanced problems. Random undersampling or SMOTE approaches are combined with rotation forest in the proposed algorithms, which balance the uneven distribution of data sets and keep the diversity of single classifier as well. Focused on two-class highly imbalanced problems, 22 relevant data sets are performed in experiments. Experimental results and statistical analyses show that our proposed methods overtake the state-of-theart ensemble methods on the most widely used imbalanced measure criterion AUC. © Copyright 2016 Inderscience Enterprises Ltd.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

From standard alpha-stable Lévy motions to horizontal visibility networks: dependence of multifractal and Laplacian spectrum

引用

Journal of Statistical Mechanics: Theory and Experiment 2018年第5期2018卷

作者： Hai-Long Zou Zu-Guo Yu Vo Anh Yuan-Lin Ma Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Hunan 411105 People's Republic of China School of Electrical Engineering and Computer Science Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia Author to whom any correspondence should be addressed. School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia

In recent years, researchers have proposed several methods to transform time series (such as those of fractional Brownian motion) into complex networks. In this paper, we construct horizontal visibility networks (HVNs) based on the -stable Lévy motion. We aim to study the relations of multifractal and Laplacian spectrum of transformed networks on the parameters and of the -stable Lévy motion. First, we employ the sandbox algorithm to compute the mass exponents and multifractal spectrum to investigate the multifractality of these HVNs. Then we perform least squares fits to find possible relations of the average fractal dimension , the average information dimension and the average correlation dimension against using several methods of model selection. We also investigate possible dependence relations of eigenvalues and energy on , calculated from the Laplacian and normalized Laplacian operators of the constructed HVNs. All of these constructions and estimates will help us to evaluate the validity and usefulness of the mappings between time series and networks, especially between time series of -stable Lévy motions and HVNs.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Dejun Guo Hesheng Wang Weidong Chen Ming Liu Zeyang Xia Kam K. Leang DARC (Design Automation Robotics & Control) Lab University of Utah Robotics Center Salt Lake City Utah USA State Key Laboratory of Robotics and System (HIT) Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong China Institute of Biomedical and Health Engineering Chinese Academy of Sciences Shenzhen China

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Cameras Robot vision systems Kinematics Mobile robots Calibration Automation

来源：评论

学校读者我要写书评

暂无评论

A novel quantum information hiding protocol based on entanglement swapping of high-level Bell states

引用

Chinese Physics B 2015年第5期24卷 231-238页

作者：徐淑奖陈秀波王连海钮心忻杨义先 Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center (National Supercomputer Center in Jinan) Information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and Telecommunications State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences

Using entanglement swapping of high-level Bell states, we first derive a covert layer between the secret message and the possible output results of the entanglement swapping between any two generalized Bell states, and then propose a novel high-efficiency quantum information hiding protocol based on the covert layer. In the proposed scheme, a covert channel can be built up under the cover of a high-level quantum secure direct communication （QSDC） channel for securely transmitting secret messages without consuming any auxiliary quantum state or any extra communication resource. It is shown that this protocol not only has a high embedding efficiency but also achieves a good imperceptibility as well as a high security.

关键词： quantum information hiding quantum covert＇channel entanglement swapping high-level Bell states

来源：评论

学校读者我要写书评

暂无评论

Blind Image Quality Assessment via Convolutional Neural Network

Blind Image Quality Assessment via Convolutional Neural Netw...

引用

International Symposium on Computational Intelligence and Design, ISCID

作者： Meiyin Wu Li Chen College of Computer Science and Technology Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China

ISBN: (纸本)9781509035595

This paper proposed a novel blind image quality assessment method that is created by training a convolutional neural network to learn discriminant features of image quality and fitting the features with a support vector regression to get an evaluation score. The pooling procedure is help to reduce the feature dimension and improve computation efficiency. The proposed method does not need any hand-crafted features contrast with most previous BIQA methods. It achieves better performance than previous BIQA methods on LIVE database. The experimental results show that the proposed method has good consistency, robustness and efficiency.

关键词： Feature extraction Image quality Databases Distortion Training Kernel Robustness

来源：评论

学校读者我要写书评

暂无评论

A spatial-constrained multi-target regression model for human brain activity prediction

引用

Applied Informatics 2016年第1期3卷 1-9页

作者： Zhenfu Wen Yuanqing Li Center for Brain Computer Interfaces and Brain Information Processing South China University of Technology Guangzhou China Guangzhou Key Laboratory of Brain Computer Interaction and Applications South China University of Technology Guangzhou China

Analyzing functional magnetic resonance imaging (fMRI) data from the encoding perspective provides a powerful tool to explore human vision. Using voxel-wise encoding models, previous studies predicted the brain activity evoked by external stimuli successfully. However, these models constructed a regularized regression model for each single voxel separately, which overlooked the intrinsic spatial property of fMRI data. In this work, we proposed a multi-target regression model that predicts the activities of adjacent voxels simultaneously. Different from the previous models, the spatial constraint is considered in our model. The effectiveness of the proposed model is demonstrated by comparing it with two state-of-the-art voxel-wise models on a publicly available dataset. Results indicate that the proposed method can predict voxel responses more accurately than the competing methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：