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Laplacian coordinates-based motion transition for data-driven motion synthesis

IET Image Processing 2012年第9期6卷 1331-1337页

作者： Yi, P. Zhang, Q. Wei, X. School of Mechanical and Engineering Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

As a fundamental technique in data-driven (or example-based) methods, motion blending has been employed to produce new motion clip from two or more clips or introduced as a medium to improve the final result of other method, for example, motion graphs. As methods of motion blending always require the system or users to classify the motion samples, it is difficult to accomplish motion blending automatically and to preserve local details, such as angular accelerations of joints of original motions. In this study, the authors developed a framework based on Laplacian coordinates to produce transitions between two motion clips, emphasising on preserving local details, without any need of motion classification. At first, multidimensional Laplacian coordinates are introduced to present local details of joints' angle. Then an error function is deduced to measure how much result motions differ from original ones in local details. By minimising such error function, new motions can then finally generated, which can preserve local details of input motion clips as much as possible. The following experiments show the effectiveness of the authors' framework. © The Institution of Engineering and Technology 2012.

关键词： Laplace transforms

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designing Uncorrelated Address Constrain for DNA Storage by DMVO Algorithm

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IEEE/ACM Transactions on Computational Biology and Bioinformatics 2022年第2期19卷 866-877页

作者： Cao, Ben Ii, Xue Zhang, Xiaokang Wang, Bin Zhang, Qiang Wei, Xiaopeng Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Ministry of Education School of Software Engineering Dalian University Dalian116622 China School of Computer Science and Technology Dalian University of Technology Dalian116024 China

At present, huge amounts of data are being produced every second, a situation that will gradually overwhelm current storage technology. DNA is a storage medium that features high storage density and long-term stability and is now considered to be a feasible storage solution. Errors are easily made during the sequencing and synthesis of DNA, however. In order to reduce the error rate, novel uncorrelated address constrain are reported, and a Damping Multi-Verse Optimizer (DMVO)algorithm is proposed to construct a set of DNA coding, which is used as the non-payload. The DMVO algorithm exchanges objects through black/white holes in order to achieve a stable state and adds damping factors as disturbances. Compared with previous work, the coding set obtained by the DMVO algorithm is larger in size and of higher quality. The results of this study reveal that the size of the DNA storage coding set obtained by the DMVO algorithm increased by 4-16 percent, and the variance of the melting temperature decreased by 3-18 percent. © 2004-2012 IEEE.

关键词： Damping

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Digital image watermarking robust to geometric attacks based on Wavelet domain

Digital image watermarking robust to geometric attacks based...

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2010 IEEE 5th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2010

作者： Ma, Na Zhang, Qiang Li, Ying Key Laboratory of Advanced Design and Intelligent Computing Dalian university Ministry of Education Province Dalian 116622 China

ISBN: (纸本)9781424464388

This paper presents a new wavelet domain watermarking method, the carrier image using wavelet decomposition. After the Walsh transform low frequency wavelet coefficients, calculated by block adaptive embedding strength, modify the wavelet coefficients of each block, and then do singular value decomposition (SVD), repeat on embedded watermark in the singular value. Fractional part of the anti-transformed image is saved, correction of the watermarked image can be accurately extracted watermark. The experimental results demonstrate that the proposed algorithm can effectively resist cutting, scaling, translation and other geometric attacks, attacks in general are also robust. © 2010 IEEE.

关键词： Singular value decomposition

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A Text Structure-based Extractive And Abstractive Summarization Method 7

A Text Structure-based Extractive And Abstractive Summarizat...

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7th International Conference on intelligent computing and Signal Processing, ICSP 2022

作者： Yan, Jing Zhou, Shihua Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian China

ISBN: (纸本)9781665478571

Extraction summarization and abstraction summarization have advantages and disadvantages, so how to better combine these two ways has become a difficult problem. To address this challenge, this paper proposed a new fusion method. The major novelty lies in the design of the new method. Wherein our approach, first, use the text structure information and the idea of the K-means algorithm to divide the text into regions, and then the main part and the non-main parts are determined according to the distribution of the subject words. Next, apply information extraction on the main part and text generation on the non-main parts. Finally, the two parts of the summarization are merged according to the sequence of the text. Experimental results show that the quality of the summarization is better than that of extraction summarization and abstraction summarization. In addition, to make the method more targeted in Chinese text processing, the Cw2vec model based on Chinese stroke information is used in the encoding process, and the experiment proves that the quality of summarization can be further improved. © 2022 IEEE.

关键词： Text processing

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SCFNet: A Spatial-Channel Features Network Based on Heterocentric Sample Loss for Visible-Infrared Person Re-identification 16th

SCFNet: A Spatial-Channel Features Network Based on Heteroc...

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16th Asian Conference on Computer Vision, ACCV 2022

作者： Su, Peng Liu, Rui Dong, Jing Yi, Pengfei Zhou, Dongsheng Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China

ISBN: (纸本)9783031262838

Cross-modality person re-identification between visible and infrared images has become a research hotspot in the image retrieval field due to its potential application scenarios. Existing research usually designs loss functions around samples or sample centers, mainly focusing on reducing cross-modality discrepancy and intra-modality variations. However, the sample-based loss function is susceptible to outliers, and the center-based loss function is not compact enough between features. To address the above issues, we propose a novel loss function called Heterocentric Sample Loss. It optimizes both the sample features and the center of the sample features in the batch. In addition, we also propose a network structure combining spatial and channel features and a random channel enhancement method, which improves feature discrimination and robustness to color changes. Finally, we conduct extensive experiments on the SYSU-MM01 and RegDB datasets to demonstrate the superiority of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Infrared imaging

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A Color Image Encryption Algorithm Based on Complementary Map and Iterative Convolutional Code 24

A Color Image Encryption Algorithm Based on Complementary Ma...

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8th International Conference on Machine Learning and Soft computing, ICMLSC 2024

作者： Xie, Yanlu Zhou, Shihua Lv, Hui Wang, Bin Che, Chao Zhang, Qiang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China

ISBN: (纸本)9798400716546

Encryption is a valid means to safeguard the safety of images, and for color images, encryption should be performed considering the intrinsic correlation between R, G, and B components. In this paper, we propose an image encryption algorithm based on a complementary map and an iterative convolutional code. Firstly, the plain image is input into the convolutional encoders for iteration to generate the correctional secret key. Secondly, we design a new complementary map. From the test data, the new chaotic map has passed the NIST testing, exhibits a good chaotic characteristic, and has a wider range of chaotic parameters. Thirdly, global scrambling is performed on the color image to disrupt the distribution between R, G, and B. Then, a row-layer and a column-layer are randomly selected to form a set of elements to be encrypted. Finally, performing global diffusion on the image further increases the safety of our scheme. Experimental results show that our algorithm has a preferable encryption effect and elevated safety. © 2024 ACM.

关键词： Convolutional codes

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Palmprint recognition based on sparse two-dimensional local discriminant projections

Palmprint recognition based on sparse two-dimensional local ...

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2014 International Conference on Applied Sciences, Engineering and Technology, ICASET 2014

作者： Zhang, Jian Xin Zhang, Zhan Ge Liu, Jian Yang Key Lab of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

ISBN: (纸本)9783038351849

A novel palmprint recognition method based on sparse two-dimensional local discriminant projections (S2DLDP) is proposed. After a description of the basic theory and resolution method for S2DLDP, the paper presents the detail palmprint feature extraction method based on S2DLDP, and tests the algorithm performance by various non-zero elements size and neighborhood size. S2DLDP considerers the class information, local separability, two-dimensional image inherent properties of training samples and sparse projection, which provides an intuitive, semantic and interpretable feature subspace for palmprint representation. The optimal recognition accuracy of EER=2.2% is obtained on PolyU palmprint database, which also illuminates the effectiveness of the proposed algorithm. © (2014) Trans Tech Publications, Switzerland.

关键词： Palmprint recognition

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Research on orbit maneuver strategies of onorbit service vehicle for multispacecraft rendezvous mission

Research on orbit maneuver strategies of onorbit service veh...

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2014 International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SMTA 2014

作者： Li, Yue Zhang, Jianxin Zhang, Qiang Wei, Xiaopeng Key Lab of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian China

ISBN: (纸本)9781845649821

In consideration of the different servicing types and various orbital spatial relationships, the paper proposes an orbital maneuver strategies model of on-orbit service vehicle (OSV) based on multiple decision variables for the problem of multispacecraft rendezvous mission. We establish a variety of mathematical models of orbit maneuver strategies, and formulate the appropriate time energy’s numerical model for different service types, adding orbital spatial relationship and service type as design variables, finally determine the optimal maneuver strategies of OSV. The paper selects two interim circle orbits as example. We select the orbit transfer strategies for service vehicle. We also calculate the relationship of transfer time and energy consumption according to the time energy’s consumption requirements. © 2014 WIT Press.

关键词： Vehicles

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GA based optimal design for megawatt-class wind turbine gear train 8th

GA based optimal design for megawatt-class wind turbine gear...

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8th International Conference on Image and Graphics, ICIG 2015

作者： Zhang, Jianxin Zhang, Zhange Key Lab of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

ISBN: (纸本)9783319219622

In this paper, we propose a novel megawatt-class wind turbine gear train optimal design method based on genetic algorithm. Firstly, we construct an objective function to obtain the optimal quality of gear train with the constrain conditions of ratio, adjacency, assemble, gear bending fatigue and gear surface contact fatigue limitations. Then, genetic algorithm is applied to achieve the optimal parameter of the objective function. Finally, the finite element analysis method is taken to verify the feasibility of the optimization results. One type of wind turbine gearbox is given as the detail example to verify the effective of proposed method, and the verification results show that the presented method can achieve good effect for wind turbine gearbox. © Springer International Publishing Switzerland 2015.

关键词： Wind turbines

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Classification of ECG signals based on 1D convolution neural network 19

Classification of ECG signals based on 1D convolution neural...

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19th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2017

作者： Li, Dan Zhang, Jianxin Zhang, Qiang Wei, Xiaopeng Key Lab of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China

ISBN: (纸本)9781509067046

Recently, with the obvious increasing number of cardiovascular disease, the automatic classification research of Electrocardiogram signals (ECG) has been playing a significantly important part in the clinical diagnosis of cardiovascular disease. In this paper, a 1D convolution neural network (CNN) based method is proposed to classify ECG signals. The proposed CNN model consists of five layers in addition to the input layer and the output layer, i.e., two convolution layers, two down sampling layers and one full connection layer, extracting the effective features from the original data and classifying the features automatically. This model realizes the classification of 5 typical kinds of arrhythmia signals, i.e., normal, left bundle branch block, right bundle branch block, atrial premature contraction and ventricular premature contraction. The experimental results on the public MIT-BIH arrhythmia database show that the proposed method achieves a promising classification accuracy of 97.5%, significantly outperforming several typical ECG classification methods. © 2017 IEEE.

关键词： Neural network models

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