检索结果-内蒙古大学图书馆

Water Splitting: Optical and Electrical Enhancement of Hydrogen Evolution by MoS2@MoO3Core–Shell Nanowires with Designed Tunable Plasmon Resonance (Adv. Funct. Mater. 32/2018)

引用

advanced Functional Materials 2018年第32期28卷

作者： Shaohui Guo Xuanhua Li Xingang Ren Lin Yang Jinmeng Zhu Bingqing Wei State Key Laboratory of Solidification Processing Center for Nano Energy Materials School of Materials Science and Engineering Northwestern Polytechnical University and Shaanxi Joint Lab of Graphene (NPU) Xi'an 710072 China Northwestern Polytechnical University‐Queen Mary University of London (NPU‐QMUL) Joint Research Institute of Advanced Materials and Structures (JRI‐AMAS) Xi'an 710072 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University No. 3 Feixi Road Hefei Anhui Province 230039 P. R. China Department of Mechanical Engineering University of Delaware Newark DE 19716 USA

来源：评论

学校读者我要写书评

暂无评论

Graphene Structure: Unconventional Atomic Structure of Graphene Sheets on Solid Substrates (Small 42/2019)

引用

Small 2019年第42期15卷

作者： Jinjin Zhang Yizhou Yang Shuo Yang Jie Song Ying Wang Xiaoguo Liu Qingqing Yang Yue Shen Shuo Wang Haijun Yang Junhong Lü Bin Li Haiping Fang Ratnesh Lal Daniel M. Czajkowsky Jun Hu Guosheng Shi Yi Zhang Zhangjiang Lab Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai 201210 China Key Laboratory of Interfacial Physics and Technology Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai 201800 China Shanghai Applied Radiation Institute Shanghai University Shanghai 200444 China Institute of Nano Biomedicine and Engineering Shanghai Engineering Research Centre for Intelligent Diagnosis and Treatment Instrument Department of Instrument Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China Materials Science and Engineering University of California San Diego La Jolla CA 92093 USA Key Laboratory of Salt Lake Resources Chemistry of Qinghai Province Qinghai Institute of Salt Lakes Chinese Academy of Sciences Xining Qinghai 810008 China State Key Laboratory for Oncogenes and Bio-ID Center School of Biomedical Engineering Shanghai Jiao Tong University Shanghai 200240 China

来源：评论

学校读者我要写书评

暂无评论

Robust lip segmentation based on complexion mixture model 1

引用

17th Pacific-Rim Conference on Multimedia, PCM 2016

作者： Hu, Yangyang Lu, Hong Cheng, Jinhua Zhang, Wenqiang Li, Fufeng Zhang, Weifei Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai China School of Computer Science Shanghai Engineering Research Center for Video Technology and System Fudan University Shanghai China Shanghai University of Traditional Chinese Medicine Shanghai201203 China

ISBN: (数字)9783319488905

ISBN: (纸本)9783319488899

Lip image analysis plays a vital role in Traditional Chinese Medicine (TCM) and other visual and speech recognition applications. However, if the lip images contain weak color difference with background parts or the background is complicated, most of the current methods are difficult to robustly and accurately segment the lip regions. In this paper, we propose a lip segmentation method based on complexion mixture model to resolve this problem. Specifically, we use the pixels’ color of the upper (lip-free) part of the face as training data to build a corresponding complexion Gaussian Mixture Model (GMM) for each face image in lab color space. Then by iteratively removing the complexion pixels not belonging to the lip region in the lower part of the face based on the GMM, an initial lip can be obtained. We further build GMMs on the initial lip and non-lip regions, respectively. The background probability map can be obtained based on the GMMs. Finally, we extract the optimal lip contour via a smooth operation. Experiments are performed on our dataset with 1000 face images. Experimental results demonstrate the efficacy of the proposed method compared with the state-of-art lip segmentation methods. © Springer International Publishing AG 2016.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Robust low-rank tensor factorization by cyclic weighted median

引用

Science China(information Sciences) 2015年第5期58卷 145-155页

作者： MENG DeYu ZHANG Biao XU ZongBen ZHANG Lei GAO ChenQiang Institute for Information and System Sciences and Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Department of Computing Hong Kong Polytechnic University Chongqing Key Laboratory of Signal and Information Processing Chongqing University of Posts and Telecommunications

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.

关键词： tensor factorization low-rank weighted median filter tensorface

来源：评论

学校读者我要写书评

暂无评论

Video saliency prediction with optimized optical flow and gravity center bias

Video saliency prediction with optimized optical flow and gr...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Zhe Wu Li Su Qingming Huang Bo Wu Jian Li Guorong Li Key Lab on Big Data Mining and Knowledge Management University of Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing Institute of Computing Technology Beijing China Capital Medical University Beijing China Beijing University of Posts and Telecommunications China Beijing

ISBN: (纸本)9781467372596

Dynamic videos are viewed fundamentally different from static images. Besides spatial features, motion feature also plays an important role as a temporal factor. Most existing video saliency models usually employ optical flow to represent the motion feature. However, optical flow often suffers from the discontinuity problem. And we also notice that human fixations in one single video frame are much sparser than that in an identical still picture. However, many spatial saliency models take each video frame as static image independently. In this paper, we predict the dynamic visual saliency by fusing spatial and temporal features. In order to construct the temporal relationships among a set of successive frames, we introduce a smoothness operator in optical flow field to obtain more accurate motion feature. Then, considering the sparse property of video saliency, we adapt the weights of the regions surrounding to the saliency gravity center in the final maps. The experiments show that our model is more consistent with humans eye-tracking benchmarks than the state-of-the-art models.

关键词： Optical imaging Gravity Computational modeling Visualization Biomedical optical imaging Adaptation models Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Color Image Segmentation Based on Modified Kuramoto Model

引用

Procedia Computer Science 2016年 88卷 245-258页

作者： Xiaojie Liu Yuanhua Qiao Xianghui Chen Jun Miao Lijuan Duan College of Applied Sciences Beijing University of Technology Beijing 100124 China Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing 100190 China College of Computer Science and Technology Beijing University of Technology Beijing 100124 China

A new approach for color image segmentation is proposed based on Kuramoto model in this paper. Firstly, the classic Kuramoto model which describes a global coupled oscillator network is changed to be one that is locally coupled to simulate the neuron activity in visual cortex and to describe the influence for phase changing by external stimuli. Secondly, a rebuilt method of coupled neuron activities is proposed by introducing and computing instantaneous frequency. Three oscillating curves corresponding to the pixel values of R, G, B for color image are formed by the coupled network and are added up to produce the superposition of oscillation. Finally, color images are segmented according to the synchronization of the oscillating superposition by extracting and checking the frequency of the oscillating curves. The performance is compared with that from other representative segmentation approaches.

关键词： Kuramoto model Neural Network Color image segmentation

来源：评论

学校读者我要写书评

暂无评论

A Hierarchical Emotion Regulated Sensorimotor Model:Case Studies

A Hierarchical Emotion Regulated Sensorimotor Model:Case Stu...

引用

第28届中国控制与决策会议

作者： Junpei Zhong Rony Novianto Mingjun Dai Xinzheng Zhang Angelo Cangelosi Centre for Robotics and Neural Systems Plymouth University Laboratory for Intelligent Dynamics and Representation Waseda University Centre of Quantum Computation and Intelligent Systems University of Technology Shenzhen Key Lab of Advanced Communication and Information Processing and Shenzhen Key Laboratory of Media Security Shenzhen University School of Electrical and Information Engineering Jinan University

ISBN: (纸本)9781467397155

Inspired by the hierarchical cognitive architecture and the perception-action model(PAM)[14],we propose that the internal status acts as a kind of common-coding representation which affects,mediates and even regulates the sensorimotor *** regulation can be depicted in the Bayesian framework,that is why cognitive agents are able to generate behaviours with subtle differences according to their emotion or recognize the emotion by perception.A novel recurrent neural network called recurrent neural network with parametric bias units(RNNPB) runs in three modes,constructing a two-level emotion regulated learning model,was further applied to testify this theory in two different cases.

关键词： Embodied Emotion Modelling Cognitive Architecture Recurrent Neural Networks Non-verbal Emotion Expression Social Robotics

来源：评论

学校读者我要写书评

暂无评论

Classification Based on Multilayer Extreme Learning Machine for Motor Imagery Task from EEG Signals

引用

Procedia Computer Science 2016年 88卷 176-184页

作者： Lijuan Duan Menghu Bao Jun Miao Yanhui Xu Juncheng Chen College of Computer Science and Technology Beijing University of Technology Beijing 100124 China Beijing Key Laboratory of Trusted Computing National Engineering Laboratory for Critical Technologies of Information Security Classified Protection Beijing 100124 China Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing 100190 China Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data Beijing 100124 China

Classification of motor imagery electroencephalogram (EEG) is one of the most important technologies for BCI. To improve the accuracy, this paper introduces a classification system based on Multilayer Extreme Learning Machine (ML-ELM). In the system, the combination of PCA and LDA is chosen as the method of feature extraction and the ML-ELM is used to classify. The ML-ELM has not only the advantage which ELM has but also better performance than ELM. In the experiment, our method is compared with the methods based on ELM, such as kernel-ELM, Constrained-ELM and V-ELM, and some state-of–the-art methods on the same dataset. The experimental results show that ML-ELM is much more suitable for motor imagery EEG data and has better performance than the others.

关键词： Electroencephalogram Classification Motor Imagery Extreme Learning Machine Multilayer Extreme Learning Machine

来源：评论

学校读者我要写书评

暂无评论

An improved reference point sampling method on Pareto optimal front

An improved reference point sampling method on Pareto optima...

引用

Congress on Evolutionary Computation

作者： Cheng He Linqiang Pan Hang Xu Ye Tian Xingyi Zhang Laboratory of Image Information Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei China Huazhong University of Science and Technology Wuhan Hubei CN Department of Computer Science Xiamen University Xiamen Fujian China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei Anhui China

ISBN: (纸本)9781509006243

In this paper, we propose a sampling approach of reference points used for performance metrics of multi-objective evolutionary algorithms. Traditional reference point sampling methods, such as the Das and Dennis method, usually sample the reference points via a set of uniformly distributed weight vectors generated on an ideal hyper-plane in objective space, which however often ignore the geometric shape of a specific Pareto front. Therefore, we propose a novel reference point sampling approach by taking the specific shape of the Pareto optimal front to be tackled into account for measuring the performance of multi-objective evolutionary algorithms. The performance of the proposed reference point sampling method against the other two state-of-the-art sampling methods is tested on six test instances in various conditions, which clearly demonstrate the effectiveness and superiority of the proposed sampling method.

关键词： Sampling methods Shape Convergence Evolutionary computation Optimization Euclidean distance

来源：评论

学校读者我要写书评

暂无评论

Expenditure aware rating prediction for recommendation

Expenditure aware rating prediction for recommendation

引用

IEEE International Conference on Big Data

作者： Chuan Shi Bowei He Menghao Zhang Fuzhen Zhuang Philip S. Yu Naiwang Guo Beijing Key Lab of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Intelligent Information Processing CAS Beijing China University of Illinois at Chicago IL USA State Grid Shanghai Electric Power Research Institute Shanghai China

ISBN: (纸本)9781467390064

The rating score prediction is widely studied in recommender system, which predicts the rating scores of users on items through making use of the user-item interaction information. Besides the rating information between users and items, lots of additional information have been employed to promote recommendations, such as social relation and geographic location. Expenditure information on each transaction between users and items is widely available on e-commerce websites, often appearing next to the rating information, while there is seldom study on the correlation between expenditures and rating scores. In this paper, we first study their correlations in real data sets and propose the expenditure aware rating prediction problem. From the data sets crawled from a well-known social media platform Dianping in China, we find some insightful correlations between expenditures and rating scores: 1) transactions or experiences with higher expenditures usually lead to higher rating scores; 2) when the real expenditures are higher than users' normal spending behavior, the users usually give higher scores; and 3) there are multiple grades of expenditure behaviors. Based on these three observations, we propose an Expenditure Aware Rating Prediction method (EARP), based on low-rank matrix factorization, to effectively incorporate the expenditure information. Extensive experiments on five real data sets show that EARP not only always outperforms other state-of-the-art baselines but also discovers the latent characteristics of users and businesses.

关键词： Correlation Pricing Electronic mail Recommender systems Social network services Big data

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：