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8th International Conference on image and Graphics, ICIG 2015

作者： Si, Dandan Hu, Yuanyuan Gan, Zongliang Cui, Ziguan Liu, Feng Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9783319219622

Single image super resolution (SR) aims to estimate high resolution (HR) image from the low resolution (LR) one, and estimating accuracy of HR image gradient is very important for edge directed image SR methods. In this paper, we propose a novel edge directed image SR method by learning based gradient estimation. In proposed method, the gradient of HR image is estimated by using the example based ridge regression model. Recognizing that the training samples of the given sub-set for regression should have similar local geometric structure based on clustering, we employ high frequency of LR image patches with removing the mean value to perform such clustering. Moreover, the precomputed projective matrix of the ridge regression can reduce the computational complexity further. Experimental results suggest that the proposed method can achieve better gradient estimation of HR image and competitive SR quality compared with other SR methods. © Springer International Publishing Switzerland 2015.

关键词： Optical resolving power

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Robust face hallucination via similarity selection and representation 8th

Robust face hallucination via similarity selection and repre...

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8th International Conference on image and Graphics, ICIG 2015

作者： Liu, Feng Yin, Ruoxuan Gan, Zongliang Chen, Changhong Tang, Guijin Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9783319219684

Face image super resolution, also referred to as face hallucination, is aiming to estimate the high-resolution (HR) face image from its low-resolution (LR) version. In this paper, a novel two-layer face hallucination method is proposed. Different from the previous SR methods, by applying global similarity selecting, the proposed approach can narrow the scope of samples and boost the reconstruction speed. And the local similarity representation step make the method have better ability to suppress noise for applications under severe condition. As a general framework, other useful algorithms can also be incorporated into it conveniently. Experiments on commonly used face database demonstrate our scheme has better performance, especially for noise face image. © Springer International Publishing Switzerland 2015.

关键词： Computers

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Stereoscopic images quality assessment based on deep learning

Stereoscopic images quality assessment based on deep learnin...

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IEEE Visual communications and image processing (VCIP)

作者： Kai Wang Jun Zhou Ning Liu Xiao Gu Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University

ISBN: (纸本)9781509053179

With the popularity of stereoscopic 3D (S3D) images and videos, many advanced objective quality assessment methods have been proposed to evaluate viewers' Quality of Experience (QoE). Among them, most algorithms take advantages of the disparity maps to extract useful features. On the other hand, deep learning has been one of the hottest research topics during these years, but limited efforts focused on the field in objective quality evaluation of S3D images. In this paper, we propose a S3D image quality assessment (S3D IQA) method based on deep learning. In this method, the Convolutional Restricted Boltzmann Machines (CRBM) combined with Factored Third-Order RBM (FTO-RBM) is considered as learning model to extract feature maps from pre-processed left and right images automatically. Then an improved traversal algorithm based on two pooling strategies is put forward to optimize extracted feature maps, which improves the final quality assessment performance significantly. Experimental results show that our S3D IQA method achieves good performance on 3D databases tested.

关键词： Feature extraction Training Databases Machine learning image quality Three-dimensional displays Data preprocessing

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Analysis of alpha rhythm epileptic Electroencephalogram based on Inner composition alignment

Analysis of alpha rhythm epileptic Electroencephalogram base...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Yiyi He Danqin Xing Jiaqin Wang Jia-Fei Dai Jun Wang Feng-Zhen Hou Image Processing and Image Communications Key Lab Nanjing Univ.of Posts & Telecomm. Nanjing General Hospital of Nanjing Military Command School of Science China Pharmaceutical University

ISBN: (纸本)9781510823808

The EEG signal is an important tool for the diagnosis and prediction of epilepsy due to EEG containing a large number of physiological and pathological *** on alpha rhythm multi-channel EEG(electroencephalogram),this paper applied inner composition alignment(IOTA) algorithm to construct brain functional network and visualize the network *** is to apply the algorithm to calculate and analyze IOTA coefficient,the node average degree and clustering coefficient of epileptic brain network for studying if epileptic brain network is significantly different from those of *** results show that IOTA coefficient of epileptic brain network obviously differs from the normal by calculating T testing with SPSS software,which proved that the effectiveness of the algorithm to distinguish IOTA coefficient of epileptic brain network.

关键词： alpha rhythm Electroencephalogram epileptic Inner composition alignment

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Comparison of regressors on 3D visual discomfort prediction

Comparison of regressors on 3D visual discomfort prediction

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Runfeng Huang Jun Zhou Xiao Gu Ya Zhang Alan C. Bovik Shanghai Key Laboratory of Digital Media Processing and Transrnissions Shanghai China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Laboratory for Image and Video Engineering University of Texas at Austin Austin USA

ISBN: (纸本)9781467390453

Most stereoscopic 3D (S3D) image visual discomfort predictors use the Support Vector Regressor (SVR) as the regression model. However, there are other good regression models such as the Random Forests (RF) and Gradient Boost Regression Tree (GBRT). Here we study the efficacy of these regression models for S3D image visual discomfort prediction. We deployed several regression models to predict the visual discomfort scores on S3D images using three kinds of features extracted from the images in the IEEE-SA and EPFL S3D image databases. So the prediction performance was evaluated to compare the performance of the different regression models. We also studied the issue of over-fitting which can affect model performance. The comparison results show that it is feasible and reliable to apply Random Forests or GBRT for S3D visual discomfort prediction with better performance than SVR.

关键词： Visualization Feature extraction Kernel Predictive models Vegetation Radio frequency Analytical models

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Coupling analysis of epileptic EEG signals based on the multiscale mutual model entropy

Coupling analysis of epileptic EEG signals based on the mult...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Ning Ji Jia-Fei Dai Jun Wang Feng-Zhen Hou Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm. Nanjing General Hospital of Nanjing Military Command School of Science China Pharmaceutical University

ISBN: (纸本)9781510823808

The Multiscale Mutual Model Entropy algorithm is presented to quantify the coupling degree between two EEG time series collected at the same time on different *** extracted the characteristics of EEG signals from the healthy and epileptics based on the *** results show that the entropy value of healthy people is higher than that of *** with the increase of scale,the difference in entropy value between them is more *** indicates that Multiscale Mutual Entropy can distinguish the coupling difference between normal samples and case samples,which is significant for the clinical pathological assessment and brain disease diagnosis.

关键词： multiscale epileptic coupling mutual model entropy

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Beta wave of sleep electroencephalogram analysis based on sign series entropy

Beta wave of sleep electroencephalogram analysis based on si...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Min Zhao Yuting Li Lu Yang Jia-Fei Dai Jun Wang Feng-Zhen Hou Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm. Nanjing General Hospital of Nanjing Military Command School of Science China Pharmaceutical University

ISBN: (纸本)9781510823808

Sleep and wake EEG have some *** studying their brain waves and calculating the sign series entropy,we use the T test for the detection of sleep and wake EEG data to figure out whether they are *** beta waves being filtered out by the filter,we calculate the entropy of the sign *** results of T test show that the beta waves in the state of sleep and wake are different.

关键词： sleep EEG sign series entropy

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Sleep EEG analysis Based on the Multiscale Jenson-Shannon Divergence

Sleep EEG analysis Based on the Multiscale Jenson-Shannon Di...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Zhengxia Zhang Jia-Fei Dai JunWang Feng-Zhen Hou Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm. Nanjing General Hospital of Nanjing Military Command School of Science China Pharmaceutical University

ISBN: (纸本)9781510823808

Sleep EEG signals analysis is a hotspot of research recently,this paper,by using nonlinear dynamics theory knowledge,JSD algorithm and multi-scale JSD algorithm is proposed for some individual conscious period and NREM sleep stage I analyzed the research of EEG signals,and the use of SPSS statistical software to verify the veracity and reliability of the experiment,at the same time,with the error bar graph method to analysis the two different states of sleep EEG signals,the results show that both the JSD algorithm and the multi-scale JSD algorithm can effectively distinguish between awake and NREM sleep stage I of EEG signals,these two conditions' EEG signals exist significant differences,The algorithm we proposed can be further used in the study of sleep EEG in installment,which can also provide all kinds of disease diagnosis and treatment of sleep with effective auxiliary function,the research has important practical significance in the future.

关键词： multi-scale JSD sleep EEG signals

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A Manipulator Design Optimization Based on Constrained Multi-objective Evolutionary Algorithms

A Manipulator Design Optimization Based on Constrained Multi...

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International Conference on Industrial Informatics, Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII)

作者： Yang Xiao Zhun Fan Wenji Li Shen Chen Lei Zhao Honghui Xie Key Lab of Digital Signal and Image Processing of Guangdong Province Shantou University Shantou Guangdong Shantou University Shantou Guangdong CN

ISBN: (纸本)9781509035762

In order to achieve high performance of robotic manipulators, light-weight and high manipulability are two essential indicators. In this paper, a model of UR5 (Universal Robot) manipulator is defined and analyzed with focus on optimizing the total mass and manipulability. The kinematics and dynamics for the robotic manipulator are used to calculate the joints torque and define quantitative measures of manipulability. Then, a design optimization problem is formulated for UR5 manipulator. It adopts the weight and manipulability of the manipulator as the objective functions. The drive train constraints associate with joint motors and gearboxes have also been considered. Finally, constrained multi-objective evolutionary algorithms (CMOEAs) are employed to solve the formulated problem. Several reasonable optimal combinations of geometrical parameters and type selection of motor and gearbox are provided. And compare them with the original structure of UR5.

关键词： Service robots Manipulator dynamics Mathematical model Design optimization Kinematics

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Evolutionary computation in China： A literature survey

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CAAI Transactions on Intelligence Technology 2016年第4期1卷 334-354页

作者： Maoguo Gong Shanfeng Wang Wenfeng Liu Jianan Yan Licheng Jiao Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent InJormation Processing Xidian University P.O. Box 224 Xi'an 710071 China

Evolutionary computation （EC） has received significant attention in China during the last two decades. In this paper, we present an overview of the current state of this rapidly growing field in China. Chinese research in theoretical foundations of EC, EC-based optimization, EC-based data mining, and EC-based real-world applications are summarized.

关键词： Evolutionary computation Evolutionary algorithms Optimization Data mining

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